System, method and apparatus for focus selection using image differences

Abstract

The present invention is entitled "System, method and apparatus for focus selection using image differences". Embodiments of the present disclosure generally relate to automatic focus selection in a multi-imager environment. Embodiments include methods, systems and apparatus configured to capture a first image of a visual object with a background associated with the object via a first image sensor. A characteristic difference between the visual object in the first image and the background in the first image is determined, and a distance determination mode is selected based on the determined characteristic difference. Accordingly, a distance to the object is calculated based on the selected distance determination mode, and a second image sensor is controlled based on the calculated distance to the object to capture a second image of the object.

Description

Technical Field

[0001] Embodiments of the present disclosure relate generally to methods and systems for imaging using multiple image sensors, and more particularly to focus selection using image differences for such methods and systems. Background Art

[0002] In an imaging device, a lens is typically designed and arranged so that an object within a specific predetermined range appears in focus through the lens. An image sensor is utilized to capture image data representing the field of view through the lens. Typically, when an object to be imaged is beyond the focus of the lens, the lens needs to be moved to one or more other focus positions to bring the object into focus. In order to provide the ability to change focus, conventional implementations for variable focus remain bulky, slow, and / or susceptible to damage from one or more environmental effects. In this regard, conventional variable focus lenses have limited operability and are unable to adapt to different imaging conditions. Summary of the invention

[0003] In general, embodiments of the present disclosure provided herein are configured for automatic focus selection in a multi-imager (or multi-image sensor) environment. The exemplary embodiments described and illustrated herein provide a fast and automatic focus selection mechanism and scheme for an imaging engine having multiple image sensors. Some exemplary embodiments relate to focus selection estimation based on image differences between images obtained from different sensors of a multi-imager imaging engine. Other specific implementations of one or more of the alternative focus selections and / or alternative focus schemes will be or will become apparent to those skilled in the art by examining the following figures and detailed description. All such additional specific implementations included within this specification are intended to be within the scope of the present disclosure.

[0004] According to some exemplary embodiments, an imaging method is provided herein. The method may be implemented using any of numerous specific implementations, such as via hardware, software, and / or firmware of a multi-sensor imaging engine and / or a multi-sensor imaging device as described herein. In some exemplary specific implementations of the method, the exemplary method includes capturing a first image of a visual object having a background associated with an object by a first image sensor. The exemplary method also includes determining a characteristic difference between the visual object in the first image and the background in the first image, and selecting a distance determination mode from a first mode and a second mode based on the determined characteristic difference. The exemplary method also includes calculating a distance to the object based on the selected distance determination mode, and controlling a second image sensor to capture a second image of the object based on the calculated distance to the object.

[0005] Additionally or alternatively, in some embodiments of the method, determining the characteristic difference includes determining an intensity difference between a first intensity of the visual object in the first image and a second intensity of the background in the first image.

[0006] Additionally or alternatively, in some embodiments of the method, selecting the distance determination mode includes selecting the first mode as the distance determination mode in response to the intensity difference being greater than or equal to a threshold, and selecting the second mode as the distance determination mode in response to the intensity difference being less than the threshold.

[0007] Additionally or alternatively, in some embodiments of the method, the first mode includes calculating the depth of the visual object in the first image as the distance to the object. Additionally or alternatively, in some embodiments of the method, the second mode includes determining a first position of the object in the first image, capturing a third image of the object by a second image sensor, determining a second position of the object in the third image, and calculating the distance to the object based on the first position and the second position.

[0008] Additionally or alternatively, in some embodiments of the method, the method further comprises calculating a distance to the object based on imaging distances of the first image sensor and the second image sensor.

[0009] Additionally or alternatively, in some embodiments of the method, calculating the distance to the object based on the first position and the second position includes calculating a first image offset of the first image based on the first position; calculating a second image offset of the second image based on the second position; and calculating the distance to the object based on the first image offset and the second image offset.

[0010] Additionally or alternatively, in some embodiments of the method, the method further comprises changing a focus position of the second image sensor based on the calculated distance to the object.

[0011] Additionally or alternatively, in some embodiments of the method, the method further includes capturing, by a second image sensor, a second image of the object from the changed focus position, and decoding the second image to extract information encoded in the object.

[0012] Additionally or alternatively, in some embodiments of the method, the visual object is a sight projection, the object comprises an informational indicia, the first image sensor comprises a near-field image sensor, and the second image sensor comprises a far-field image sensor.

[0013] According to some exemplary embodiments, an imaging system is provided herein. In an exemplary embodiment, the imaging system includes: a memory configured to store executable instructions; and one or more processors configured to execute the executable instructions. In some exemplary embodiments, the one or more processors are configured to obtain a first image of a visual object with a background associated with an object from a first image sensor. In some exemplary embodiments, the one or more processors are further configured to determine a characteristic difference between the visual object in the first image and the background in the first image, and select a distance determination mode from a first mode and a second mode based on the determined characteristic difference. In some exemplary embodiments, the one or more processors are further configured to calculate the distance to the object based on the selected distance determination mode, and control the second image sensor based on the calculated distance to the object to capture a second image of the object.

[0014] Additionally or alternatively, in some embodiments of the imaging system, to determine the characteristic difference, the one or more processors are configured to determine an intensity difference between a first intensity of the visual object and a second intensity of the background.

[0015] Additionally or alternatively, in some embodiments of the imaging system, to select the distance determination mode, the one or more processors are configured to select the first mode as the distance determination mode in response to the intensity difference being greater than or equal to a threshold. Alternatively, in some exemplary embodiments of the imaging system, to select the distance determination mode, the one or more processors are configured to select the second mode as the distance determination mode in response to the intensity difference being less than a threshold.

[0016] Additionally or alternatively, in some embodiments of the imaging system, the first mode includes instructions for calculating the depth of the visual object in the first image as a distance to the object.

[0017] Additionally or alternatively, in some embodiments of the imaging system, the second mode includes instructions for determining a first position of the object in the first image, obtaining a third image of the object from a second image sensor, determining a second position of the object in the third image, and calculating a distance to the object based on the first position and the second position.

[0018] Additionally or alternatively, in some embodiments of the imaging system, the one or more processors are further configured to calculate a distance to the object based on imaging distances of the first image sensor and the second image sensor.

[0019] Additionally or alternatively, in some embodiments of the imaging system, in order to calculate the distance of an object based on a first position and a second position, the one or more processors are configured to calculate a first image offset of the first image based on the first position, calculate a second image offset of the second image based on the second position, and calculate the distance of the object based on the first image offset and the second image offset.

[0020] Additionally or alternatively, in some embodiments of the imaging system, the one or more processors are further configured to change a focus position of the second image sensor based on the calculated distance to the object.

[0021] Additionally or alternatively, in some embodiments of the imaging system, the one or more processors are further configured to obtain a second image of the object from the changed focus position from a second image sensor and decode the second image to extract information encoded in the object.

[0022] In some exemplary embodiments, an imaging device is provided. In an exemplary embodiment, the device includes a first image sensor, a second image sensor, and a controller. In some exemplary embodiments, the first image sensor is configured to capture a first image of a visual object with a background associated with an object. In some exemplary embodiments, the controller is configured to obtain a first image from the first image sensor, determine a characteristic difference between the visual object in the first image and the background in the first image, and select a distance determination mode from a first mode and a second mode based on the determined characteristic difference. In some exemplary embodiments, the controller is further configured to calculate the distance to the object based on the selected distance determination mode, and control the second image sensor to capture a second image of the object based on the calculated distance. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Having thus generally described embodiments of the present disclosure, reference will now be made to the accompanying drawings, which are not necessarily drawn to scale, and in which:

[0024] FIG. 1A illustrates a block diagram of an exemplary multi-sensor imaging system according to an exemplary embodiment of the present disclosure;

[0025] FIG1B illustrates a block diagram of an exemplary multi-sensor imaging engine according to an exemplary embodiment of the present disclosure;

[0026] Figure 2 A block diagram of an exemplary multi-sensor imaging device according to an exemplary embodiment of the present disclosure is shown;

[0027] Figure 3 shows a visualization of a field of view associated with an exemplary multi-sensor imaging device according to an exemplary embodiment of the present disclosure;

[0028] Figure 4A shows a perspective view of an exemplary multi-image sensor imaging device according to an exemplary embodiment of the present disclosure;

[0029] Figure 4B shows a perspective component view of image sensors of an exemplary multi-sensor imaging device according to an exemplary embodiment of the present disclosure;

[0030] Figure 5 Another perspective component view of an image sensor of an exemplary multi-sensor imaging device is shown according to an exemplary embodiment of the present disclosure;

[0031] Figure 6 shows a crosshair projection of a multi-sensor imaging device according to an exemplary embodiment of the present disclosure;

[0032] Figure 7 A flow chart depicting an exemplary operation of an imaging process according to an exemplary embodiment of the present disclosure is shown;

[0033] Figure 8 A flow chart depicting exemplary operations of a process for focus control in a multi-imager environment is shown according to an exemplary embodiment of the present disclosure;

[0034] Fig.9A An exemplary image captured by a near-field image sensor for determining an intensity difference between a visual object and a background of the object is shown;

[0035] Fig. 9B An exemplary scheme for measuring distances to objects in a scene is shown; and

[0036] FIG. 10 shows a flow chart depicting exemplary operations of an imaging method with image difference based autofocus selection according to an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0037] Embodiments of the present invention will now be described more fully hereinafter with reference to the accompanying drawings, in which some, but not all, embodiments of the present disclosure are shown. Indeed, embodiments of the present disclosure can be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that the present disclosure will satisfy applicable legal requirements. Throughout the text, like reference numerals refer to like elements.

[0038] Imaging devices and systems have been applied in more complex and advanced fields than simple photography. There is a constant need to improve the imaging capabilities of these devices and systems to accommodate new capabilities. While some solutions have proposed minimizing errors and noise in existing configurations, other solutions aim to add more components to support new capabilities. One such solution involves using multiple image sensors to image different aspects of a scene. Each image sensor requires a different focusing mechanism to capture the field of view with appropriate clarity. Appropriate focus selection requires estimating the depth of the object to be captured. However, due to changes in imaging conditions, a depth estimation technique suitable for one type of imaging condition may not be suitable for estimating the depth of an object under other types of imaging conditions. Therefore, relying on only one type of depth estimation technique may not be sufficient to meet imaging requirements in different imaging conditions. Therefore, such imaging devices and systems have limited operability for image capture.

[0039] Imaging devices (such as tag readers) are used in a variety of scenarios, each of which requires a set of specific imaging requirements to be met so that operations associated with the tag reader, such as symbol decoding, can be continuously performed. Due to the variety of application areas of imaging readers, there are a large number of imaging conditions in which such devices are used. The operability of these devices is limited by the types of imaging conditions in which they can successfully process the captured images. Effective image processing requires effective image capture, which is in turn controlled by several imaging factors (such as focus, exposure, lighting, etc.). In addition, for such devices, it is preferred to perform image capture and image processing in the shortest possible duration. One way to shorten this duration is to speed up the image processing task by using efficient algorithms and hardware. However, given the limited form factor, weight, and power available for such devices, such upgrades are limited. Therefore, for devices limited by form factor and / or size and available power, it is desirable to capture images suitable for image processing The time spent is as short as possible. To this end, it is desirable that the time required to adjust the optical components is short so that the image sensor quickly focuses on the object without the need for additional components.

[0040] Imaging devices and systems utilize visual objects (such as a sight projection) to determine the distance to the object being imaged so that the image sensor can therefore focus on the object based on the determined distance to the object. Often, current scene conditions, such as when used in a high ambient light environment, may result in a situation where the sight projection cannot be distinguished from the background. Therefore, it becomes a challenge to correctly focus the imaging device on the object being imaged. Even predetermined focus positions / step sizes may not be beneficial because directly searching for the appropriate focus may require additional time and processing, which can delay the overall image capture process.

[0041] Some embodiments described herein relate to autofocus selection in a multi-image sensor environment including multiple image sensors. Some embodiments described herein provide a device for calculating the distance from an imaging system to a target or object to determine the autofocus setting of one or more optical components of a multi-image sensor environment. Some embodiments utilize a sight projection to center an object or target along a desired axis. The sight projection can be based on a structured beam that projects a pattern onto one or more regions in a scene along the optical axis of the imaging system. If the object or target is close to a horizontal plane containing the optical axis, this allows the object or target to be in focus. For example, some exemplary sight pattern shapes may include, but are not limited to, a laser beam (spot) coinciding with the optical axis, a laser fan (line) coinciding with the horizontal plane containing the optical axis, and two (for example) parallel, spaced lines, one of which is located above and one below the horizontal plane containing the optical axis. When the object or target is located between the two lines, its resulting image on the corresponding image sensor is in focus.

[0042] Some embodiments described herein utilize images captured by a near-field image sensor of an imaging engine to determine whether a sight projection is distinguished from a background, and perform selection of a distance determination mode based on the intensity difference between the sight captured in the near-field image and the background captured in the near-field image. The embodiment further performs an estimation of the distance to the object or target according to the selected mode, thereby performing focus selection of the imaging engine in the far field based on the estimated distance. The embodiment further utilizes a far-field image sensor with focus adjustment to capture an image of the object or target for further processing. For example, the captured image can be used to decode information encoded in the object or target. In some exemplary embodiments, the image captured by the far-field image sensor with focus adjustment can be combined with the image captured by the near-field image to produce a stereoscopic image. Some embodiments can utilize multiple near-field image sensors and multiple far-field image sensors, and the process for distance estimation can be extended to the accumulation of image difference calculations for each pair of near-field image sensors and far-field image sensors. In some exemplary embodiments, the process for determining the characteristic difference can be averaged for each near-field image sensor so that the trigger factor for selecting the appropriate distance determination mode is correctly determined. In some exemplary embodiments, the processing of image differences may also be averaged for all near-field image sensors and far-field image sensors.

[0043] In some embodiments, one or more events may be triggered to indicate situations where distance estimation may be required using a visual object such as a sight projection. In this regard, one or more characteristic differences between a visual object and its background may be used to determine lighting conditions in a scene. If the lighting conditions indicate that the visual object is distinguished from the background at an acceptable level, a less stringent distance estimation method may be relied upon to calculate the distance to the object or target. For example, the intensity difference between pixels corresponding to the visual object in the near-field image and pixels corresponding to the background in the near-field image (especially pixels near the boundary pixels of the visual object) may be determined to determine lighting conditions. In a similar manner, other parameters that contribute to determining the distinctiveness of the visual object and the background may be utilized.

[0044] In some exemplary embodiments, if the lighting conditions indicate that the visual object cannot be distinguished from the background at an acceptable level, a process for determining the image difference between the images of each image sensor of the imaging engine can be utilized. To this end, the near-field image can be decoded to determine the location of the object or target in the near-field image. In parallel, another image from the far-field image sensor can be captured and decoded to determine the location of the object or target in the far-field image. The image difference can then be expressed in terms of the location of the object or target in the two images, which in turn can be used to determine the distance to the object or target. Therefore, the corresponding focus position of the far-field image sensor can be determined, and the object or target can be imaged from this focus position to capture a decodable image of the object or target.

[0045] In such cases, the change to another distance estimation mode helps save considerable time and resources required to search directly for the focus position. This improves the response time of the imaging device for decoding information. In addition, since the exemplary embodiments do not require unnecessary movement of the focus mechanism (such as a focus motor), the exemplary embodiments result in significant power savings and / or noise reduction in the captured images.

[0046] Some embodiments utilize the difference between images captured by the stereo cameras of a multi-sensor imaging engine to calculate the distance to an object. Obtaining the distance from the image difference requires correcting the images from the stereo cameras before determining the difference. This normalizes the images so that they appear to be taken from parallel, matched cameras, regardless of their actual extrinsic and intrinsic parameters. This allows the difference to be simply measured as a horizontal feature offset between the corrected images. Based on this horizontal difference measurement of the object features in the image, a suitable technique such as a normal triangulation operation can be used to determine the distance to the object. The determined distance can in turn be used to make appropriate focus selections for one or more image sensors of the multi-sensor imaging engine.

[0047] Such embodiments provide efficient focus selection using minimal additional computation. Operation of such embodiments captures images in a manner likely to enable successful completion of image processing tasks (such as mark or symbol scanning) while increasing the likelihood that images will be captured within a desired operating time frame that includes sufficient data for successful processing. By implementing the various exemplary embodiments described herein, the operating efficiency of the imaging device is maintained or improved while addressing challenges caused by the use of multiple sensors and changing imaging conditions.

[0048] In some embodiments, some of the operations described above may be modified or further amplified. In addition, in some embodiments, additional optional operations may also be included. The modification, amplification or addition of the operations described above may be performed in any order and in any combination.

[0049] [definition]

[0050] The term "illumination" refers to one or more rays of light generated by an illumination source within a defined field of view. In at least one exemplary context, illumination includes one or more illumination pulses generated by a corresponding illumination source. In some embodiments, illumination is generated based on a "defined pulse frequency," which refers to the rate of illumination pulses generated by the illumination source. Additionally or alternatively, in some embodiments, illumination is generated based on a "defined pulse phase," which refers to an activation period during which the illumination source generates the corresponding illumination. Thus, an illumination period may refer to the duration during which an illumination source corresponding to an illumination pulse remains activated.

[0051] The term "illumination source" (also referred to as an "illuminator source" or "illuminator") refers to one or more light generating hardware, devices, and / or components configured to produce illumination within a desired field of view. Non-limiting examples of illumination sources include one or more light emitting diodes (LEDs), lasers, etc. One or more illumination sources may be dedicated to or common to each image sensor and / or projection optics of a multiple image sensor system.

[0052] The term "near-field illumination source" refers to an illumination source configured to generate illumination to illuminate a near field of view associated with a near-field image sensor. In at least one exemplary context, the near-field illumination source is configured to generate illumination in a wider field of view than a far-field illumination source.

[0053] The term "far-field illumination source" refers to an illumination source configured to generate illumination to illuminate a far field of view associated with a far-field imager. In at least one exemplary context, the far-field illumination source is configured to generate illumination in a narrower field of view than a near-field illumination source.

[0054] The term "near-field illumination" refers to the specific illumination produced by a near-field illumination source. In some embodiments, the near-field illumination is associated with the illumination of the near field of view captured by the near-field image sensor.

[0055] The term "far-field illumination" refers to the specific illumination produced by a far-field illumination source. In some embodiments, the far-field illumination is associated with the illumination of a far field of view captured by a far-field image sensor.

[0056] The term "imager" or "imaging module" refers to one or more components configured to capture an image representing a particular field of view. In at least one exemplary context, the imager includes at least one optical component (e.g., a lens and / or associated housing) that defines the particular field of view. Additionally or alternatively, in at least one exemplary context, the imager includes an image sensor configured to output an image based on light, such as that engaged with the image sensor via the optical component.

[0057] The term "image sensor" refers to one or more components configured to generate an image represented by a data object based on light incident on the image sensor. In some such exemplary contexts, the image sensor converts light waves interacting with the image sensor into signals representing an image output by the sensor.

[0058] The term "near-field image sensor" refers to an image sensor configured to capture an image of a near field of view. In at least one context, the near-field image sensor includes at least one near-field optical component that defines the near field of view, and an electronic sensor. In at least one exemplary context, the near-field image sensor may include a global shutter. In some exemplary contexts, the near-field image sensor may include a rolling shutter. The term "near-field image" refers to electronic data generated by the near-field image sensor, which electronic data embodies a captured representation of a scene in the near field of view.

[0059] The term "far-field image sensor" refers to an image sensor configured to capture an image of a far field of view. In at least one context, the far-field image sensor includes at least one far-field optical component that defines the far field of view, and an electronic sensor. In at least one exemplary context, the far-field image sensor may include a rolling shutter. In some exemplary contexts, the far-field image sensor may include a global shutter. The term "far-field image" refers to electronic data generated by the far-field image sensor, the electronic data embodying a captured representation of a scene in the far field of view.

[0060] The term "exposure period" or simply "exposure" refers to electronic data representing the length of time that the image sensor is configured to be exposed to the incoming light. In at least one exemplary embodiment, the image sensor of the imager is configured to utilize a variable exposure time that can be set to a specific exposure time value.

[0061] The term "visual object" refers to a projected pattern or object projected by an imager into a scene to aid in image capture. In at least one exemplary embodiment, the visual object may be a sight projection (hereinafter also referred to as a sight).

[0062] The term "object" or "target" refers to one or more regions of interest in a scene being imaged. In some example embodiments, an object is optically distinguishable from the background of the scene being imaged.

[0063] The term "characteristic difference" refers to the difference between two regions in an image, expressed as the difference between the image characteristics of each region. Such image characteristics may include, but are not limited to, intensity, sharpness, pixel count, etc. In some exemplary embodiments, the characteristic difference between two regions in an image may correspond to an intensity difference between the two regions in the image. In some exemplary embodiments, the characteristic difference between two regions in an image may be determined by a pixel-to-pixel analysis of each such region.

[0064] The technical personnel in the field of the present disclosure will think of many modifications and other embodiments of the present disclosure set forth herein after benefiting from the teachings presented in the foregoing description and the related drawings. Therefore, it should be understood that the embodiments are not limited to the specific embodiments disclosed, and modifications and other embodiments are intended to be included within the scope of the appended claims. In addition, although the above description and the related drawings describe example embodiments in the context of certain example combinations of elements and / or functions, it should be understood that different combinations of elements and / or functions can be provided by alternative embodiments without departing from the scope of the appended claims. In this regard, for example, it is also conceivable to combine elements and / or functions different from those explicitly described above, as can be shown in some of the appended claims. Although specific terms are used herein, they are used only in a general and descriptive sense, not for the purpose of limitation.

[0065] FIG. 1A shows a block diagram of an exemplary multi-sensor imaging system 10 (hereinafter, also referred to as imaging system 10) according to an exemplary embodiment of the present disclosure. The multi-sensor imaging system 10 includes an imaging engine 100 communicatively coupled to a controller 20, a communication interface 40, an activation component 60, and one or more peripheral components 80. In some exemplary embodiments, the imaging system 10 may include a plurality of Figure 1AThe imaging system 10 may include fewer or more components as shown. The imaging system 10 is configured to capture one or more images of a target in one or more fields of view using one or more illumination sources. The imaging system 10 processes the one or more images to perform one or more image processing tasks, such as indicia reading. Thus, in some exemplary embodiments of the present disclosure, the imaging system 10 may be partially or fully embodied as a indicia or symbol reader or a handheld device capable of reading indicia and similar symbols. Figure 2 An exemplary embodiment of the imaging system 10 is shown in FIG. 1 , the details of which will be described in subsequent portions of this disclosure.

[0066] The controller 20 may be configured to perform one or more control operations associated with the imaging system 10. For example, the controller 20 may control the imaging engine 100 to cause an image capture of a target in the field of view of the imaging engine 100. Additionally, the controller 20 may process the captured image to perform one or more image processing tasks. The controller 20 may be embodied as a central processing unit (CPU) including one or more processors and a memory. In some exemplary embodiments, the controller 20 may be implemented as one or more of various hardware processing devices using one or more microcontroller units (MCUs), such as a coprocessor, a microprocessor, a digital signal processor (DSP), a processing element with or without an accompanying DSP, or various other processing circuits, including integrated circuits, such as, for example, ASICs (application specific integrated circuits), FPGAs (field programmable gate arrays), hardware accelerators, dedicated computer chips, etc. In some embodiments, the processor of the controller 20 may include one or more processing cores that are configured to operate independently. A multi-core processor may implement multiple processing within a single physical package. Additionally or alternatively, the processor may include one or more processors configured in tandem via the bus to enable independent execution of instructions, pipelining, and / or multithreading.

[0067] The memory may be non-transitory and may include, for example, one or more volatile memories and / or non-volatile memories. For example, the memory may be an electronic storage device (e.g., a computer-readable storage medium) comprising a gate configured to store data (e.g., bits) that can be retrieved by a machine (e.g., a computing device such as a processor). The memory may be configured to store information, data, content, applications, instructions, etc. for enabling the device to perform various functions according to exemplary embodiments of the present invention. For example, the memory may be configured to buffer data for processing by the processor. Additionally or alternatively, the memory may be configured to store instructions for execution by the processor.

[0068] The processor (and / or a coprocessor or any other processing circuit that assists the processor or is otherwise associated with the processor) can communicate with the memory via a bus for transferring information between components of the imaging system 10. The processor can be configured to execute instructions stored in the memory or otherwise accessible to the processor. Additionally or alternatively, the processor can be configured to perform hard-coded functions. Therefore, whether configured by hardware methods or software methods, or by a combination of them, the processor can represent an entity (e.g., physically embodied in the form of a circuit) that can perform operations according to an embodiment of the present invention while being configured accordingly. Therefore, for example, when the processor is embodied as an ASIC, FPGA, etc., the processor can be a specially configured hardware for performing the operations described herein. Alternatively, for example, when the processor is embodied as an executor of software instructions, the instructions can specifically configure the processor to perform the algorithms and / or operations described herein when executing the instructions. Among other things, the processor may also include a clock, an arithmetic logic unit (ALU), and logic gates configured to support the operation of the controller 20.

[0069] The communication interface 40 may include an input interface and an output interface for supporting communication to and from the imaging system 10. The communication interface 40 may be any device, such as a device or circuit embodied in hardware or a combination of hardware and software, which is configured to receive and / or transmit data to / from a communication device that communicates with the imaging system 10. In this regard, the communication interface 40 may include, for example, an antenna (or multiple antennas) and support hardware and / or software for implementing communication with a wireless communication network. Additionally or alternatively, the communication interface 40 may include a circuit for interacting with the antenna to cause the transmission of a signal via the antenna or processing the reception of a signal received via the antenna. In some environments, the communication interface 40 may alternatively or additionally support wired communication. Thus, for example, the communication interface 40 may include a communication modem and / or other hardware and / or software for supporting communication via a cable, a digital subscriber line (DSL), a universal serial bus (USB), or other mechanisms.

[0070] The activation component 60 may include hardware, software, firmware, and / or a combination thereof configured to instruct a user to initiate (and / or terminate) a desired function. For example, the activation component 60 may transmit an activation signal to cause the controller 20 to begin operation of the imaging engine 100, such as beginning illumination by one or more illumination sources, and / or capturing one or more images by an image sensor. Additionally or alternatively, the activation component 60 may transmit a deactivation signal to the controller 20 to terminate the corresponding function, such as stopping scanning via the image sensor. In some embodiments, the activation component 60 is embodied as one or more buttons, triggers, and / or other physical components disposed in or on the body of the base. For example, in at least one exemplary context, the activation component 60 is embodied as one or more "trigger" components that, when an operator engages these trigger components (e.g., when an operator squeezes a trigger), transmits a signal to the controller 20 to initiate a corresponding function. In some such embodiments, when the operator disengages the components (e.g., when the operator releases the trigger), the activation component may transmit a deactivation signal to the controller 20 to stop such a function. Alternatively or additionally, in at least some embodiments, the activation component 60 is embodied without any components that are directly engaged by an operator. For example, when the imaging system 10 is embodied as an imaging device, the activation component 60 may be embodied as hardware and / or software, or a combination thereof, for detecting that the imaging device has been raised and / or positioned to a predefined "scanning" position, and / or lowered from that position to trigger deactivation. Alternatively or additionally, the activation component 60 may be embodied as a user interface element of the imaging system 10. In such embodiments, the activation component 60 embodied as a user interface element may be configured to receive input from a user on the user interface, and then transmit a corresponding command to the controller 20.

[0071] The one or more peripheral components 80 include other structural and functional elements of the imaging system 10, such as, for example, a display device, a user interface, a housing, a base, a power supply, etc. One or more of the peripheral components 80 may be controlled by the controller and may operate according to instructions or controls provided by the controller 20.

[0072] FIG. 1B illustrates an exemplary multi-sensor imaging engine (hereinafter also referred to as an “imaging engine”) according to an exemplary embodiment of the present disclosure. Specifically, as shown, the exemplary multi-sensor imaging engine is embodied as a multi-sensor imaging engine 100. The multi-sensor imaging engine 100 includes a plurality of image sensors, for example, a near-field image sensor and / or a far-field image sensor, which are configured to capture image data objects in a near field of view associated with the near-field image sensor and a far field of view associated with the far-field image sensor, respectively. In at least one exemplary context, the multi-sensor imaging engine 100 is configured to capture images for the purpose of tag reading in different ranges, such as a close-range range using a near-field image sensor and a long-range range using a far-field image sensor.

[0073] As shown, the multi-sensor imaging engine 100 includes a near-field image capture optical device 104A. The near-field capture optical device 104A may be embodied as one or more lenses and / or other optical components that are configured to enable light to laterally transmit through and interact with a corresponding image sensor (specifically, the near-field image sensor 102A). In this regard, the near-field image capture optical device 104A may define a specific field of view that can be captured by the near-field image sensor 102A. In some embodiments, the near-field image capture optical device 104A defines a near field of view associated with a first focus range, so that objects located at the first focus range and / or within a determinable offset can be clearly visible in an image captured by the near-field image sensor 102A.

[0074] In addition, as shown, the multi-sensor imaging engine 100 includes a far-field image capture optical device 104B. The far-field image capture optical device 104B may be embodied as one or more lenses and / or other optical components, which are configured to enable light to laterally penetrate and interact with the corresponding image sensor (specifically, the far-field image sensor 102B). In this regard, the far-field image capture optical device 104B may define a second field of view that can be captured by the far-field image sensor 102B. In some embodiments, the far-field image capture optical device 104B defines a far field of view associated with the second focus range, so that objects located at the second focus range and / or within a determinable offset can be clearly visible in the image captured by the far-field image sensor 102B. In some such embodiments, the near field of view is wider than the far field of view, so that the captured data is more representative of the environment within the field of view of the multi-sensor imaging engine 100. The far field of view may be narrower than the near field of view and focused at a farther range to enable more clear capture of objects located at a greater range than can be clearly captured in the near field of view.

[0075] In some exemplary embodiments, the near-field imaging sensor 102 may include a global shutter to provide enhanced motion tolerance. The near-field imaging sensor 102A may use a large field of view (FOV), which enables applications such as but not limited to optical character recognition (OCR), image reconstruction, machine learning, etc. In some embodiments, the far-field sensor 102 may include a rolling shutter. The far-field image sensor 102B uses a small FOV to improve sampling of the far field. Additionally, each of the near-field image sensor 102A and the far-field image sensor 102B may have an associated focusing mechanism. The focusing mechanism may include a focusing scheme that controls the movement of one or more focusing lenses along the optical axis direction of the image sensor (102A or 102B). To this end, in some embodiments, the focusing scheme may include one or more motion actuators, such as a stepper motor or a piezoelectric actuator. In some exemplary embodiments, the focusing scheme may be built into the lens, such as a variable (e.g., liquid) lens.

[0076] The focusing scheme may provide multiple discrete focus positions in each field of view, and a motor may move the focus optics of a particular image sensor to each of the discrete focus positions to represent a focus mechanism. For example, in some exemplary embodiments, to change the focus of far field image sensor 102B, a corresponding motor may move the associated focus optics of far field image sensor 102B to three discrete focus positions in the far field. The operation of each focus mechanism may be controlled by a processing component such as Figure 1A The controller 20 or processor 202 of the embodiment of the present invention is controlled. In some exemplary embodiments, when the lens has a built-in focusing solution, the processing component can use the estimated distance data to control the focus of the lens.

[0077] In some embodiments, for example, as shown in the figure, each image sensor (or a subset thereof) is associated with one or more components for generating illumination, which is configured to illuminate the field of view defined by the image sensor. For example, as shown in the figure, the multi-sensor imaging engine 100 further includes a near-field illumination source 1 06A and a corresponding near-field projection optical device 1 08A. The near-field illumination source 1 06A is configured to generate light in the direction of the optical axis of the near-field projection optical device 1 08A. The light is refracted through the near-field projection optical device 1 08A to generate near-field illumination, which can be generated as a desired pattern based on the configuration and design of the near-field projection optical device 1 08A. In this regard, the illumination generated by the light leaving the near-field projection optical device 108A can illuminate a specific field of view, such as a near field of view that can be captured by the near-field image sensor 102A.

[0078] Similarly, the multi-sensor imaging engine 100 further includes a far-field illumination source 106B and a corresponding far-field projection optical device 108B. The far-field illumination source 106B is configured to generate light in the direction of the far-field projection optical device 108B. The light is refracted through the far-field projection optical device 108B to generate far-field illumination, which can be generated as a desired pattern based on the configuration and design of the far-field projection optical device 108B. In this regard, the far-field illumination can illuminate a specific field of view, such as a far field of view that can be captured by the far-field image sensor 102B.

[0079] Additionally, in some embodiments, the multi-sensor imaging engine 100 further includes an aimer illumination source 110. The aimer illumination source 110 is configured to generate light in the direction of the aimer projection optics 112. For example, the aimer illumination source includes one or more laser diodes and / or high-intensity LEDs that are configured to generate sufficiently powerful and / or concentrated light. The light is refracted through the aimer projection optics 112 to generate aimer illumination, which can be generated as a desired pattern based on the configuration and design of the aimer projection optics 112. In an example context, for purposes such as barcode scanning, the aimer pattern can be generated as a laser line pattern, a laser dot pattern, as two parallel lines enclosing a limited area therebetween, etc.

[0080] The multi-sensor imaging engine 100 also includes a protective window 114. The protective window 114 includes one or more optical components configured to enable generated light to exit the engine 100 and to enable incident light to be received, for example, through the image capture optics 104A and 104B to interact with the corresponding image sensors 102A and 102B.

[0081] It should be understood that in other embodiments, the multi-sensor imaging engine may include any number of image capture optics, image sensors, illumination sources, and / or any combination thereof. In this regard, the imaging engine 100 may be expanded to capture any number of fields of view, each of which may be associated with a corresponding illuminator designed to specifically illuminate the corresponding field of view. One or more of the illumination sources may adversely affect the operation of another illuminator. In such cases, when one such illumination source is activated, the adversely affected image sensor may be activated between illumination pulses of the illumination source, as described herein. Such operations may be implemented in any combination of illumination sources and image sensors.

[0082] In some embodiments, the multi-sensor imaging engine 100 includes one or more processing components (e.g., processors and / or other processing circuits) for controlling activation of one or more components of the multi-sensor imaging engine 100. For example, in at least one exemplary embodiment, the multi-sensor imaging engine 100 includes a processor configured to time illumination pulses of the near-field illumination source 106A and / or the far-field illumination source 106B, and / or control exposure of the near-field image sensor 102B and / or the far-field image sensor 102A. In some such contexts, the processor is embodied as any of a myriad of processing circuit implementations, such as an FPGA, an ASIC, a microprocessor, a CPU, and the like. In at least some embodiments, the processor may communicate with one or more memory devices having computer coded instructions that, when executed by the processor, implement such functions. In some embodiments, it should be understood that the processor may include one or more sub-processors, remote processors (e.g., "cloud" processors), and the like, and / or may communicate with one or more additional processors for performing such functions. For example, in at least one embodiment, the processor may communicate with another processor within the imaging device (e.g., relative to a processor on a remote processor such as a "cloud" processor). Figure 2 The processor 202) shown and described above can communicate with and / or operate in conjunction with the other processor.

[0083] Figure 2 An exemplary multi-sensor imaging device 200 is shown in accordance with an exemplary embodiment of the present disclosure. As shown, the multi-sensor imaging device 200 includes a device base 210 for housing various components of the device. In this regard, it should be understood that the device base may be embodied in any of a myriad of base designs, using any of a myriad of materials, etc. to be suitable for positioning the various components of the multi-sensor imaging device 200 for operation. In at least one exemplary context, the device base 210 may be embodied as a handheld device base, a wearable base, etc.

[0084] The multi-sensor imaging device 200 includes the multi-sensor imaging engine 100 as described above with respect to FIG. 1B. The multi-sensor imaging device 200 also includes a processor 202. The processor 202 (and / or any other co-processor and / or processing circuitry assisting the processor 202 and / or otherwise associated with the processor 202) may provide processing functionality to the multi-sensor imaging device 200. In this regard, the processor 202 may be as described with respect to FIG. Figure 1A The controller 20 may be embodied in any of the numerous ways discussed above.

[0085] In some exemplary embodiments, the processor 202 is configured to provide functionality for operating one or more components of the multi-sensor imaging device 200. For example, the processor 202 may be configured to activate the far-field illumination source 106B, the near-field illumination source 106A, and / or the aimer illumination source 110. Additionally or alternatively, in some embodiments, the processor 202 is configured to activate the near-field image sensor 102A and / or the far-field image sensor 102B to expose the corresponding image sensor, and / or to read out the captured data to generate an image based on the captured data during the exposure. Additionally or alternatively, in some embodiments, the processor 202 is configured to process the captured image, for example, based on one or more image processing tasks. In one such exemplary context, the processor 202 is configured to perform an attempt to detect and decode visual markers (such as 1D and / or 2D barcodes) from the captured image. In this regard, the processor 202 may be configured to provide such functionality using a visual marker parsing algorithm and / or a visual marker decoding algorithm.

[0086] Additionally or alternatively, optionally in some embodiments, the multi-sensor imaging device 200 further includes an activation component 206. The activation component 206 may be as described with respect to Figure 1A The activation component 60 may be embodied in numerous ways as discussed above.

[0087] Additionally or alternatively, optionally in some embodiments, the imaging device 200 further includes a display 208. The display 208 may be embodied as an LCD, LED, and / or other screen device configured for data provided by one or more components of the device 200. For example, in some embodiments, the display 208 is configured to render a user interface that includes text, images, control elements, and / or other data provided by the processor 202 for rendering. In some embodiments, for example, the display 208 is embodied as an LCD and / or LED monitor that is integrated with the surface of the device base 210 and visible to the operator, for example to provide information decoded from a barcode and / or information associated with such information decoded from a barcode. In one or more embodiments, the display 208 may be configured to receive user interactions, and / or may transmit one or more corresponding signals to the processor 202 based on user interactions to trigger functions. In some such embodiments, the display 208 provides user interface functions that embody the activation component 206, for example to enable the operator to initiate and / or terminate the scanning function via interaction with the user interface.

[0088] Additionally or alternatively, optionally in some embodiments, the imaging device 200 further includes a memory 204. The memory 204 may provide storage functionality, for example to store data processed by the multi-sensor imaging device 200 and / or instructions for providing the functionality described herein. In some embodiments, the processor 202 may communicate with the memory 204 via a bus to transfer information between components of the device and / or retrieve instructions for execution. The memory 204 may refer to Figure 1A The memory 204 may be embodied in numerous ways as discussed above with respect to the controller 20 of the imaging device 200. The memory 204 may be configured to store information, data, content, applications, instructions, etc. for enabling the imaging device 200 to perform various functions according to some exemplary embodiments. In some embodiments, the memory 204 includes computer-coded instructions for execution by the processor 202, for example, to perform the functions described herein and / or in conjunction with hard-coded functions executed via the processor 202. For example, when the processor 202 is embodied as an executor of software instructions, the instructions may specifically configure the processor 202 to perform the algorithms and / or operations described herein when executing the instructions.

[0089] In some exemplary embodiments of the present disclosure, the processor 202 and the memory 204 may be embodied together as an imaging control device, and thus may be fixedly or detachably coupled to the imaging device 200, or may be partially or completely located outside the imaging device 200. In some embodiments, the imaging control device may be embodied as an integrated circuit operatively coupled to the imaging device 200.

[0090] Figure 3 1 shows a visualization of a field of view that may be captured by an exemplary multi-sensor imaging device. Figure 3 , there is shown a near field of view 302 and a far field of view 304 that can be captured by the multi-sensor imaging device 200. As shown, the near field of view 302 is wider than the far field of view, so that more of the environment can be captured within the near field of view 302 than the far field of view 304.

[0091] Furthermore, as shown, the far field of view 304 extends further than the near field of view 302. In this regard, the narrow nature of the far field of view 304 can enable a more detailed representation of a particular portion of an environment to be captured as compared to the near field of view 302. In some embodiments, a corresponding near-field image sensor and a corresponding far-field image sensor of the multi-sensor imaging device 200 can capture the near field of view 302 and the far field of view 304. The near field of view 302 can be associated with a near focus range at a particular distance from a corresponding image sensor in the multi-sensor imaging device 200. Additionally or alternatively, the far field of view 304 can be associated with a far focus range at another distance from a corresponding image sensor in the multi-sensor imaging device 200. In this regard, the near-field focus range can be closer than the far-field focus range, such that objects farther away from the multi-sensor imaging device 200 than from the near-field image sensor have better focus when captured via the far-field image sensor, thereby allowing for an extended range.

[0092] The multi-sensor imaging device 200 may be configured to provide illumination specifically for illuminating each of the fields of view 302 and 304. In this regard, the illumination source may be specifically designed to match the field of view of the corresponding image sensor such that the illumination appropriately illuminates the corresponding field of view without overflow or under-illumination. Producing illumination during illumination using another illumination source and capturing during a non-corresponding image sensor may result in overflow (e.g., when capturing using a far-field image sensor during a near-field illumination pulse) and / or under-illumination (e.g., when capturing using a near-field image sensor during a far-field illumination pulse), which may affect the quality of data in the captured image, such as due to over-illumination and / or under-illumination, as described. In this regard, the near-field illumination may be generated so as to substantially or completely illuminate the near field of view 302. The near-field illumination may be generated according to an illumination pattern that sufficiently illuminates the entire near field of view 302 for capture.

[0093] The far-field illumination may be generated so as to substantially or completely illuminate the far field of view 304. The far-field illumination may be generated according to an illumination pattern that sufficiently illuminates the entire far field of view 304 for capture by a corresponding far-field image sensor. The far-field illumination may illuminate only a certain percentage of the near field of view 302, such as a central percentage of the near field of view 302 (e.g., 25%, 50%, etc.).

[0094] Near field illumination, far field illumination, and aimer illumination may be synchronized relative to one another in a manner to ensure zero or minimal interference between associated image sensors. In this regard, the corresponding illumination sources may be appropriately controlled by controller 20 / processor 202 to ensure efficient image capture.

[0095] Some exemplary embodiments described herein provide a multi-image sensor imaging device (hereinafter also referred to as a device) having an automatic focus selection mechanism based on image differences between images of multiple image sensors of the device. Figure 4A A perspective view of an exemplary multi-image sensor imaging device according to an exemplary embodiment of the present disclosure is shown. The multi-sensor imaging device 400 may have multiple image sensors, each image sensor of the device 400 may have an associated optical element, and each image sensor together with its associated optical element may constitute a separate imaging assembly. For simplicity, the multi-sensor imaging device 400 has been shown as having two image sensor assemblies 400A and 400B. However, it is contemplated that within the scope of the present disclosure, more such image sensor assemblies may be present in the multi-sensor imaging device 400 as required. The device 400 further includes integrated illumination optics 400A1 and 400B1 for a corresponding one of the image sensors 400A and 400B. In some exemplary embodiments, the image sensor assembly 400A may be suitable for imaging in the near field of view of the device 400, while the image sensor assembly 400B may be suitable for imaging in the far field of view of the device 400. One or more components may be shared by each of the sensor assemblies 400A and 400B and thus may be provided as an integrated component in the device 400. For example, an integrated aimer optic may be provided in common with both sensor assemblies 400A and 400B. In such a configuration, the integrated component may be provided on an imaging assembly corresponding to either image sensor of the image sensor assemblies 400A and 400B.

[0096] Each image sensor of device 400 may have an associated optical element, and each image sensor together with its associated optical element may constitute a separate imaging assembly. Figure 4B A perspective component view of one image sensor of an exemplary multi-sensor imaging device 400 is shown according to an exemplary embodiment of the present disclosure. Figure 4BThe exemplary imaging assembly 400A shown in FIG. 4 may include an imaging optics 402 disposed or contained within a generally cylindrical lens barrel 404. The imaging optics 402 may include one or more optical lenses for focusing incident radiation onto an image sensor 410 for image formation. The lens barrel 404 may be slidably disposed or contained within a generally cylindrical sleeve 406. The sleeve 406 may be fixed to an imaging assembly body 408, which may provide a platform for other items such as an image sensor 410. When the lens barrel 404 moves axially within the sleeve 406, the imaging optics 402 may be focused and defocused with the image sensor 410. Thus, the imaging optics 402 may be positioned to a precise desired position within the sleeve 406 so as to focus the target with the image sensor. Depending on the position of the target relative to the imaging assembly 400, a plurality of focus positions may be defined for the imaging optics 402 for focusing the target with the image sensor 410. As previously discussed, the controller can control the movement of the imaging optics 402 to position the imaging optics at one of a plurality of focus positions depending on the position of the target relative to the imaging assembly 400. The barrel 404 is inserted into the sleeve 406 and rotated to change the position of the optics 402 along the optical axis OA to precisely position the optics 402 at a desired position relative to the image sensor 410. The barrel 404 can be controlled using the imaging optics controller ( Figure 4B 406). In some exemplary embodiments, the imaging assembly 400A may be adapted to image in the near field of view of the imaging device 400. In such configurations, the movement of the lens barrel 404 may be fully or partially restricted, and there may be no focusing mechanism. In some such configurations, the lens barrel 404 may not be present, and the stationary lens may be disposed in the sleeve 406. The exemplary imaging assembly 400 may include one or more light sources 412 for illuminating a corresponding field of view of a scene including a target. Additionally or optionally, in some exemplary embodiments, the imaging assembly 400 may include an aimer illuminator 414A and associated aimer optics 414B for projecting an aimer as a visual object onto the imaged scene. The aimer illuminator 414A may include one or more aimer LEDs that may be controlled by a controller to produce the illumination required to project the aimer as an indicator.

[0097] Figure 5 Another perspective component view of an image sensor of an exemplary multi-sensor imaging device 400 according to an exemplary embodiment of the present disclosure is shown. Specifically, Figure 5 An exploded perspective view 500 of an imaging assembly 400B including an illumination module, an optional aimer module, and an imaging module is shown. It is contemplated that other image sensors of the exemplary multi-sensor imaging device may have the same Figure 5 . According to various exemplary embodiments, the lighting module is configured to project a lighting pattern and includes an imaging lighting light source assembly 512A, which may include one or more light sources. The imaging lighting light source assembly 512A may further include one or more light source groups, each light source group including, for example, one or more light sources. In an exemplary embodiment, such light sources may illustratively include light emitting diodes (LEDs). In various embodiments, an LED having a wide variety of wavelengths and filters or any combination of wavelengths or filters may be used. Other types of light sources may also be used in other embodiments. The light source may illustratively be mounted to a printed circuit board. This may be the same printed circuit board, and the image sensor 510 may illustratively be mounted on the printed circuit board.

[0098] In various exemplary embodiments, Figure 5 As shown in the embodiment of the present invention, the lighting module may include an imaging lighting optical component 512B. The imaging lighting optical component 512B or other parts of the lighting module may include any of a variety of optical elements, such as one or more lenses, one or more diffusers, one or more reflectors and / or one or more prisms as illustrative examples. The imaging lighting optical component 512B can thereby focus, diffuse, shape or otherwise project the lighting toward a target area. The lighting module can thereby project a lighting pattern toward or on a target area. The lighting pattern thus projected can include any type or pattern of lighting in different embodiments.

[0099] A sight module may be optionally provided, particularly when the imaging assembly 400A does not have such a sight module. The sight module may be configured to project a sighting pattern and include a sighting light source 514A and sighting optical elements 514B and 514C. For example, the sighting light source 514A may include one or more light emitting diodes (LEDs) and / or aiming lasers, and the sighting optical element may include one or more apertures 514C and one or more lenses 514A, which may be, for example, spherical lenses, aspherical lenses, cylindrical lenses, or anamorphic lenses. The sight module projects light from the sighting light source 514A through the aperture 514C and the optical device 514B to provide a sighting pattern onto the target to help capture an image of the target with the image sensor 510. For example, the sighting light source 514A may project light forward into a hemispherical pattern. The front surface of the LED light source may include an integrated convex lens surface designed to reduce the angular divergence of light leaving the LED. As much of this light as possible is directed through the aimer aperture 514C and further through the aimer optics 514B. The aimer optics 514C can be designed to produce an image of the aimer aperture onto a mark located in the target. For example, in another implementation, the aimer module can include a laser and a laser collimator.

[0100] The imaging module is configured for image capture and includes an image sensor 510 and an imaging optics assembly 504, which is operable to focus an image onto the image sensor 510. The image sensor 510 may include a pixel array adapted to operate in a global shutter or full frame shutter mode or alternatively in a rolling shutter mode. The image sensor may be a color or monochrome 2D solid-state image sensor implemented in any of CCD, CMOS, NMOS, PMOS, CID, CMD, back-illuminated technologies. The image sensor may be a progressive or interlaced imager. The image sensor may include an array of photosensitive photodiodes (or pixels) that convert incident light energy into electrical charge. An exemplary image sensor may use a monochrome image sensor that may include a color filter element that defines color-sensitive pixel elements dispersed throughout the monochrome pixel array. An exemplary image sensor device may include an image sensor processor, an analog-to-digital converter (ADC), and other circuits. The imaging optics assembly 504 may include optical components such as a lens for focusing light from a target onto the image sensor 510.

[0101] The modules of the imaging assembly 500 may operate in a synchronized manner to perform image processing tasks. For example, the imaging illumination module may project an illumination pattern while the imaging module exposes a first frame of image data during an illumination exposure period. The aimer module may provide an indicator to a user of the multi-image sensor device to place a target within the indicated area for effective image capture.

[0102] Figure 6 A crosshair projection by a multi-sensor imaging device according to an exemplary embodiment of the present disclosure is shown. In some exemplary embodiments, the multi-sensor imaging device can be a smartphone 602 having multiple imaging components (such as imaging components 400 and / or 500). In this regard, the smartphone 603 can have a crosshair module integrated with the smartphone or available as an add-on module to help aim at the marker for scanning.

[0103] The aimer module includes a projection module for forming a beam from the light source module into an aiming pattern (i.e., a pattern) and for projecting the pattern onto a target (e.g., a decodable mark). The projection module may include a lens (or multiple lenses), an aperture, and / or a diffractive optical element (DOE) to help form the pattern. In some embodiments, the projection module may include a reflector (or multiple reflectors) to redirect and / or shape the beam / pattern. The pattern created by the aimer projection module provides feedback on the field of view of the camera so that when the pattern 604 is projected onto a target (e.g., a barcode 606), the user can understand the content of the imaging and how the image is aligned. To this end, the pattern may indicate the center of the camera's field of view, the edge of the camera's field of view, and / or the corner of the camera's field of view. Therefore, the pattern may include, but is not limited to, for example: a cross, a frame, a line, or a corner. In a possible embodiment, the pattern may be used to determine the lighting conditions of the scene so that a suitable distance determination mode may be selected for the focusing of the imaging device. For example, the focusing of the pattern may provide information about the camera's ability to focus on the barcode.

[0104] Figure 7 A flowchart depicting an exemplary operation of an imaging process 700 is shown in accordance with an exemplary embodiment of the present disclosure. The process 700 may be performed by referring to Figure 1A and Figure 2The described imaging system 10 or imaging device 200 is implemented. The process 700 includes, at 702, capturing, by a first image sensor, a first image of a visual object having a background associated with the object. In some exemplary embodiments where the object is placed at a certain distance from the imaging system, it is essential to determine the imaging conditions before capturing a decodable image for further image processing. In this regard, the first image sensor can be a sensor suitable for imaging in a near field of view. The first image sensor can capture the near field of view, which includes a visual object, such as a sight, a target or an object projected by a projection device, and a background of the target or the object. In the example of Figure 6 In the exemplary context shown, the first image sensor may capture images of the projected pattern 604 as well as the target barcode 606 and the background of the target barcode 606 .

[0105] Process 700 further includes, at 704, determining characteristic differences between a visual object in the first image and a background in the first image. The image captured at 702 is processed to detect the visual object and its background. Subsequently, an analysis (e.g., a pixel-by-pixel analysis of the captured image) is performed to determine one or more characteristic differences between the visual object captured in the first image and the background captured in the first image. In some exemplary embodiments, determining the one or more characteristic differences may include determining an intensity difference between pixels constituting the visual object in the captured image and pixels constituting the background in the captured image. Other examples of the one or more characteristic differences may include a difference between the clarity of the visual object and the background.

[0106] Process 700 may include, at 706, selecting a distance determination mode from the first mode and the second mode based on the determined characteristic difference. When the characteristic difference determined at 704 is significant - e.g., greater than or equal to a threshold, this indicates a situation where the visual object can be visually distinguished from the background by the imaging system. In such a situation, it is likely that the object can also be focused with the aid of the visual object. That is, the distance to the visual object can be determined using a triangulation method, and the distance can be used to determine a corresponding focus position of the imaging system in the far field of view. The calculation of the distance to the object (as the distance to the visual object) can be considered a first distance determination mode.

[0107] However, if the characteristic difference determined at 704 is not significant, for example, less than a threshold, this corresponds to a situation where the imaging conditions of the scene are not conducive to visually distinguishing the visual object from the background. For example, when the imaging system is used in a high ambient light environment (such as outdoors), the high ambient light in the imaged scene may produce a captured image that is not well distinguishable between the region of interest and the background. In such a situation, if the imaging system is focused in the far field using such captured images, it is possible that the distance to the visual object cannot be determined because the visual object cannot be tracked. Therefore, the characteristic difference determined at 704 is an important triggering factor for selecting an appropriate distance determination mode. In some exemplary embodiments where the visual object cannot be distinguished from the background (i.e., the magnitude of the characteristic difference is less than a threshold), the distance to the object is determined using an image difference between a first image sensor and another image sensor of the imaging system. Such a mode of determining the distance to an object using image differences can be considered a second distance determination mode, which will be referred to later. Figure 8 A detailed description of the second distance determination mode is provided.

[0108] Process 700 includes calculating the distance to the object based on the selected distance determination mode at 708. After selecting the appropriate distance determination mode from the first mode and the second mode, the distance to the object is calculated accordingly according to the selected mode. Figure 8 A detailed description of distance calculation is discussed.

[0109] The process 700 includes, at 710, controlling a second image sensor to capture a second image of the object based on the calculated distance to the object. The determined distance to the object is an important factor that helps determine the focus position of the image sensor. Therefore, a discrete focus step size of the second image sensor (such as a far-field image sensor) is determined corresponding to the determined distance to the object. To this end, a lookup table can be obtained by a controller executing the process 700, which provides a focus step size corresponding to the distance to the object. Once the focus position of the second image sensor is determined, the controller controls the associated optical device of the second image sensor to move to the determined focus position, and the second image sensor captures an image of a scene with the object. Therefore, the focus of the second image sensor is determined without incurring additional steps or resources. In addition, the movement of the associated optical device is only performed when needed without incurring any unnecessary motor movement, thereby saving precious onboard power and reducing the chance of noise in the resulting image due to focus adjustment. Therefore, the process 700 provides an effective measure for operating a multi-sensor imaging system / device. Therefore, the device performing or utilizing the process 700 produces improvements in imaging and / or subsequent image processing tasks.

[0110] Figure 8A flow chart depicting exemplary operations of a process 800 for focus control in a multi-imager environment is shown in accordance with at least one exemplary embodiment of the present disclosure. Process 800 may be considered a portion of process 700, with particular emphasis on the selection of a distance determination mode and the corresponding calculation of the distance. Process 800 is triggered when image capture by a first image sensor (such as a near-field image sensor) is complete and ready for further processing. For example, referring to Figure 7 In process 700, when the image capture at step 702 is completed, the controller executing process 700 can call process 800 for further processing the captured first image, the first image including an image of an object having a visual object projected thereon and a background of the object.

[0111] Process 800 includes, at 802, determining an intensity difference between a first intensity of a visual object in a first image and a second intensity of a background in the first image. As an example of a characteristic difference between the visual object and the background of an object, an intensity difference between the visual object and the background can be determined. In some exemplary embodiments, the intensity difference can be an indicator of a difference between a pixel intensity value corresponding to a pixel of the visual object in the image and a pixel intensity value corresponding to a pixel of the background in the image. The intensity value of each pixel can be a single value for a grayscale image or three values ​​for a color image. The intensity values ​​of some or all pixels of the first image can be used to determine the reference image. Fig.9A The intensity difference described.

[0112] Fig.9A An exemplary image 902 captured by a near-field image sensor is shown for determining the intensity difference between a visual object 904 and a background of an object 906. The image 902 may include an mxn array of pixels. Fig.9A As shown, by the coordinates (M p , N i )、(M q N i )、(M q N i ) and (M p N i ) corresponds to the visual object 904, which is represented as a crosshair projection. p , N i ) to (M q , N i )、(M q , N i ) to (M q , N j )、(M q , N j ) to (M p, N j ) and (M p , N j ) to (M p , N i ) defines the boundary of the visual object 904 and can therefore be considered as a boundary pixel of the visual object 904. p-1 , N i-1 ) to (M q+1 , N i-1 )、(M q+1 , N i-1 ) to (M q+1 , N j+1 )、(M q+1 , N j+1 ) to (M p-1 , N j+1 ) and (M p-1 , N j+1 ) to (M p-1 , N i-1 ) corresponds to the pixels of the background of the border pixels next to the visual object 904. These pixels may be referred to as background pixels. In some exemplary embodiments, the intensity difference between the border pixels and the background pixels may be calculated based on each pixel pair, wherein each pixel pair includes a border pixel and a background pixel next to the border pixel. In this regard, the intensity difference of each pixel pair may be determined, and the average value of the intensity difference of each pixel pair determines the intensity difference between the visual object and the background.

[0113] In some exemplary embodiments, in order to calculate the intensity difference between the visual object and the background, the first average value of the pixel intensity values ​​of all pixels corresponding to the visual object in the image and the second average value of the pixel intensity values ​​of all pixels corresponding to the background in the image can be calculated. The intensity difference can then be determined as the difference between the first average value and the second average value. In some cases, the background can cover a large number of pixels that are far away from the boundary pixels of the visual object in position. In such cases, in order to simplify the calculation, only those pixels corresponding to the background can be selected to calculate the second average value, and these pixels are within the threshold proximity of the boundary pixels of the visual object. Therefore, the intensity difference calculated in any of the aforementioned ways can be used to determine whether the visual object in the first image and the background of the first image can be distinguished with an acceptable clarity level. In this regard, the intensity difference can be compared with a threshold value to determine whether the visual object can be distinguished from the background.

[0114] Return to reference Figure 8, process 800 may include determining at 804 whether the intensity difference between the visual object and the background is greater than or equal to a threshold. The threshold may be a configurable value that may be set, for example, according to operator input or based on an imaging mode. If the lighting conditions at the time of image capture of the first image cause the visual object to be distinguished from the background in the captured image, the intensity difference may be greater than or equal to the threshold. In such a case, the result of the determination at step 804 is "yes" and control is transferred to step 806. At step 806, process 800 includes determining a first position of the object in the first image. Any suitable image processing technique and / or other machine learning technique may be used to determine the position of the object. For example, recognition of a predetermined pattern associated with an information tag may be performed in the image. Such recognition may be part of a workflow for decoding the information tag and may be referred to as a subroutine. In some exemplary embodiments, the object may be, for example, Fig.9A The step of determining the location of barcode 906 in near-field image 902 may include identifying a location within near-field image 902 that exhibits both a high concentration of edges and a high concentration of low intensity values ​​as a candidate location for a barcode.

[0115] For example, a suitable processing medium such as one or more processors or controllers that perform process 800 can process image 902 to identify edges within digital image 902. An edge is a location of digital image 902 that exhibits a high contrast transition in intensity. For example, an edge can define a transition from low intensity to high intensity (i.e., from light to dark) or from high intensity to low intensity (i.e., from dark to light). Due to the nature of barcodes, i.e., black and white (or other dark and light) patterns, barcodes produce prominent, easily detectable edges. In order to identify edges within digital image 902, the processing component can analyze image 902 to detect locations where brightness values ​​exhibit significant changes. The processing component can use conventional edge detection techniques to identify edges within image 902. For example, the processing component can apply a kernel matrix (e.g., a matrix of weights or multiplication factors) to digital image 902 to detect edges. The kernel matrix is ​​typically much smaller than the actual image to which it is applied. For example, a three-pixel by three-pixel (3×3) kernel matrix will be described. However, the barcode detection module 34 can use kernel matrices of other sizes.

[0116] In some exemplary embodiments, the 3×3 kernel matrix may be centered on each pixel of the image 902 in turn, and the pixel values ​​of the 3×3 area around the center pixel may be multiplied by the corresponding weight of the kernel matrix to generate a weighted pixel value. Next, the weighted pixel values ​​may be summed to obtain the first-order derivative of the center pixel. The processing component may compare the first-order derivative of the center pixel with a transition threshold, and detect an edge when the first-order derivative is greater than or equal to the transition threshold. If the first-order derivative is greater than or equal to the transition threshold, it is determined that the pixel is located on the edge. In one aspect, the processing component may set the pixel determined to be located at the edge to an intensity value associated with white or black, and set the pixel determined not to be located at the edge to an opposite intensity value, such as black or white. Therefore, the result of the edge detection may be an edge map, which is a binary image of the original image 902 with all details removed except for the identified edge. The binary image may be a black and white image, where the edge is white and the rest of the image is black, or vice versa, that is, the edge is black and the rest of the image is white. Although the detection of edges is described using first order derivatives of digital image 902 , any suitable edge detection technique may be used to detect edges within image 902 , such as using second order derivatives of digital image 902 .

[0117] The processing component can also process the image 902 to identify image areas with low intensity (referred to herein as "low-intensity areas"). The low-intensity areas correspond to the dark parts of the image 902. The barcode detection module 34 can identify the low-intensity areas of the image 902 via threshold processing. In particular, the barcode detection module 34 can identify the low-intensity areas of the image 902 by comparing each pixel intensity value with an intensity threshold, and filter out any pixel values ​​greater than or equal to the intensity threshold. Therefore, the result of the low-intensity detection can be a low-intensity map, which is a binary image representing the original image 902 with high-intensity areas removed. In one example, the barcode detection module 34 can set pixel intensity values ​​less than or equal to the intensity threshold to white, and set pixel intensity values ​​greater than or equal to the intensity threshold to black. In this case, the low-intensity area of ​​the image 902 is represented as a white area, and the non-low-intensity area of ​​the image 902 is represented as black. Alternatively, the low-intensity area can be represented as a black area, and other areas are represented as white areas. In some cases, the processing component can process the digital image to identify the edge and low-intensity area of ​​the image 902 in parallel.

[0118] The processing component may perform one or more morphological operations on the edge map to identify the locations of edges exhibiting high concentrations within the image 902. Similarly, the processing component may perform one or more morphological operations on the low-intensity map to identify the locations of low-intensity values ​​exhibiting high concentrations within the image 902. Morphological operations may be performed on the edge map and the low-intensity map simultaneously (i.e., in parallel) or continuously. The morphological operations may include one or more of a dilation operation, an erosion operation, an open operation, a closed operation, etc. In one example, the processing component may perform dilation on the edge map and the low-intensity map. Dilation typically fills holes and broken areas, and connects areas separated by spaces smaller than the size of the structuring element used for dilation. For binary images, a structuring element (e.g., a 3×3 structuring element) is centered on each pixel. If any pixel within the structuring element is white, the pixel value centered on the structuring element is set to white. A similar method may be performed for a grayscale image. For example, in a grayscale image, each pixel value may be recalculated using a structuring element by setting the pixel value equal to the maximum pixel value among the pixel values ​​within the structuring element. In this way, the size of bright areas surrounded by dark areas grows, and the size of dark areas surrounded by bright areas decreases. Small dark spots in the image disappear as they are "filled in" to the surrounding intensity values. The effect is most noticeable in places in the digital image where intensity changes rapidly, for example, in areas where bar codes are located.

[0119] The processing component can then combine the dilated edge map and the dilated low-intensity map. For example, the processing component can perform an "AND" operation to combine the dilated edge map and the dilated low-intensity map. The combined image represents the portion of image 902 that is identified as edges and low-intensity regions. In other words, the combined image represents the portion of the image where the edges and low-intensity regions occur simultaneously in space.

[0120] If desired, in some exemplary embodiments, the processing component may again perform one or more morphological operations on the combined image. For example, the barcode detection module 34 may perform another dilation operation on the combined image to fill holes and damaged areas and connect areas separated by spaces that are smaller than the size of the structuring element used for dilation. The processing component may also perform a flood fill operation on the combined dilated image to further fill any remaining holes within the area of ​​the combined dilated image. The flood fill operation fills holes inside an object. In some cases, the processing component may perform a closing operation instead of a flood fill operation. The closing operation closes small holes that may be within the size of the fill element, while the flood fill operation closes all holes within the object, regardless of the size of the holes. In this way, the one or more morphological operations performed on the combined image cause areas with overlapping edges and low-intensity portions to be pure white or almost pure white areas.

[0121] Then, the processing component can analyze the positions remaining in the combined image after one or more morphological operations to identify positions of the digital image that may potentially be barcodes. In other words, the processing component can determine whether the position is a candidate for a barcode. For example, the processing component can compare each position remaining in the combined image with one or more barcode standards to determine whether the position is a candidate for a barcode. For example, the processing component can compare the size of the position with the barcode size standard to determine whether the position is too small or too large to be a barcode. If the size of the position is less than a threshold, the processing component can determine that the position is not a barcode. Positions that are too small (even if the position is detected as a barcode) may not have enough details to resolve the barcode and may be discarded. As another example, the processing component can compare the shape of the position with the barcode shape standard to eliminate positions that are substantially dissimilar to the shape of a barcode (e.g., a rectangle or square). In yet another example, the processing component can compare the fill factor of the position with the barcode fill factor standard. Specifically, a square or rectangle can be placed around the position to determine how many pixels are not white relative to the surrounding rectangular area. If the percentage of pixels that are not white relative to the surrounding rectangular area exceeds a threshold percentage, the location may be eliminated from the candidate locations.

[0122] Then, by verifying whether the remaining digital image at the position has a unique barcode feature, the processing component can determine whether the remaining position is actually a barcode. In the case of some 2D barcodes, for example, the processing component can analyze the position of the image identified as a candidate for a barcode to determine whether the identified position includes a barcode finder pattern. In the case of a 2D data matrix barcode, the processing component can look for a unique peripheral pattern within the position, for example, two vertical lines composed of alternating black and white square modules. In the case of a 2D QR barcode, the processing component can look for a nested alternate light and dark square finder pattern at the three corners of the identified position. However, the processing component can analyze the identified position for other unique barcode finder patterns or other unique features associated with other barcode symbols. In addition, the processing component can analyze images other than the original image 902, such as a grayscale version of a digital image, an edge map for the generation of a unique barcode feature or pattern, or a low-intensity map generated. In this way, at step 806, the position corresponding to the barcode (i.e., object) in the image 902 can be determined and output by the processing component.

[0123] Process 800 may include capturing a third image of the object by a second image sensor at 808. The processing component may call a second image sensor different from the first image sensor to capture another image of the object. In some exemplary embodiments, the second image sensor may be an image sensor suitable for imaging in the far field of view of the imaging system. Therefore, the second image sensor may have a rolling shutter. Alternatively, in some less intensive applications, the second image sensor may even have a global shutter. The second image sensor may capture an image of a scene including the object.

[0124] Process 800 may further include, at 810, determining a second position of the object in the third image. The image captured by the second image sensor may be suitably processed by the processing component to determine the position of the object in the captured image (i.e., the third image). For example, in the exemplary case where the object may be a barcode, the processing component may perform a subprocess for determining the position of the barcode in the captured image in a manner similar to that described with reference to step 806. Thus, at step 810, the second position of the object in the third image (the image captured by the second image sensor) may be determined.

[0125] Process 800 may further include calculating, at 812, a distance to the object based on the first position determined at step 806 and the second position determined at step 810. Calculating the distance to the object requires calculating various parameters, such as a baseline between the first image sensor and the second image sensor, an imaging distance of each of the first image sensor and the second image sensor, and a respective image offset of the first image sensor and the second image sensor. In some exemplary embodiments, the distance z to the object (from the imaging system / device) may be calculated according to the following equation:

[0126]

[0127] in:

[0128] B is the baseline distance between the first image sensor and the second image sensor;

[0129] v1 and v2 are imaging distances of the first image sensor and the second image sensor, respectively;

[0130] d1 and d2 are image offsets in the first image and the third image, which are calculated based on the first position of the object and the second position of the object.

[0131] The baseline B of the first image sensor and the second image sensor can be obtained from the design of the imaging device / system. Fig. 9BAs shown, the baseline distance B between the two image sensors corresponds to the straight-line distance between the optical centers O1 and O2 of the sensors. For example, O1 can correspond to the optical center of the first image sensor, and O2 can correspond to the optical center of the second image sensor. In some exemplary embodiments, the optical center of the image sensor can be considered from the center of the area of ​​the image sensor that will be exposed to incident illumination from the scene of the image to be captured.

[0132] The distance between the optical center and the start point of the optical axis of the image sensor may define the imaging distance 'v' of the image sensor. Fig. 9B , the imaging distance v1 of the first image sensor corresponds to the straight-line distance between points O1 and C1. In a similar manner, the imaging distance v2 of the second image sensor corresponds to the straight-line distance between points O2 and C2.

[0133] The distance between the start point of the optical axis of the image sensor and the center of the object formation on the image sensor (i.e., the position of the object in the captured image) can define an image offset 'd' of the image sensor and its corresponding captured image. The image offset in the first image and the second image is a function of the position of the object in its corresponding captured image. For example, the image offset of the first image sensor is a function of the first position of the object in the first image of the object, and the image offset of the second image sensor is a function of the second position of the object in the third image. Fig. 9B , the image shift d1 of the first image may correspond to the straight-line distance between points C1 and A1. In a similar manner, the image shift d2 of the second image may correspond to the straight-line distance between points C2 and A2.

[0134] In this manner, the exemplary embodiments described herein provide an efficient process for estimating the distance to an object even when imaging conditions may not be suitable for efficient image capture.

[0135] Referring back to the determination at step 804, if the lighting conditions at the time of image capture of the first image are such that the ambient light is very high, the visual object may blend with or be suppressed by the background in the captured image. In such a case, the intensity difference may be less than the threshold, and the result of the determination at step 804 is "no", and control passes to step 814.

[0136] Process 800 may include, at 814, calculating the depth of the visual object in the first image as the distance to the object. Fig.9A When the sight 904 of the object is substantially distinguishable from the background, exemplary embodiments of the present invention may provide a less intensive process for calculating the distance to the object. In such cases, the distance to the object may be estimated as Figure 7The depth to the visual object is determined based on the image captured by the first image sensor at step 702. In this regard, the distance may be determined by any suitable method, such as, but not limited to, triangulation.

[0137] In this way, the exemplary embodiments described herein provide methods, devices, and systems for effectively determining the distance to an object by properly selecting an appropriate distance determination mode. In some exemplary embodiments, processes 700 and / or 800 may be triggered in situations where ambient lighting prevents capturing an object at a predetermined clarity level.

[0138] After calculating the distance to the object by any distance determination mode, process 800 includes changing the focus position of the second image sensor based on the calculated distance to the object at 816. The estimated distance to the object is a measure of how far the object is from the imaging device / system. Therefore, the estimated distance to the object can be used to determine the corresponding focus position of the optical device of the image sensor. If the object is located in the far field of the imaging device / system, the far field image sensor can be better suited for imaging in the far field of the imaging device / system. However, if the object is located in the near field of the imaging device / system, the near field image sensor may be a preferred choice for image capture. In some exemplary embodiments, the estimated distance to the object can be used to determine which image sensors are suitable for image capture of the object for further processing. For example, if the estimated distance to the object is less than or equal to a threshold, the near field image sensor can be used for image capture, however, if the estimated distance to the object is greater than the threshold, the far field image sensor can be used for image capture of the object. Therefore, focus selection based on the estimated distance of the selected image sensor can be performed. In this regard, the processing component can refer to a lookup table that describes the relationship between the distance to the object and the focus step size of the image sensor. Using the lookup table, the appropriate focus step size can be determined, and the specific image sensor can be moved according to the determined focus step size.

[0139] In this manner, the exemplary embodiments described herein provide methods and machines for moving an appropriate image sensor to a position where an object is in focus. Some embodiments relate to situations where ambient lighting inhibits the object from being in focus with the image sensor. The embodiments described herein provide time-efficient and energy-efficient automatic focus selection. Such embodiments consider one or more imaging conditions to select a best fit mode for determining the depth of an object, and perform focus selection according to the selected best fit mode.

[0140] FIG. 10 illustrates an exemplary workflow of a tag decoding process performed by an exemplary multi-sensor imaging system according to at least one exemplary embodiment of the present disclosure. In some exemplary embodiments, imaging system 10 and / or imaging device 200 may include or be part of an exemplary symbol reading device (such as a tag reader). Process 1000, as shown in FIG. 10, provides a method for symbol decoding that includes aspects of methods 700 and 800. When implementing process 1000, a symbol reader having multiple image sensors is able to mitigate issues with autofocus selection that arise in a multi-imager environment, and is therefore able to provide a fast and energy efficient autofocus solution and error-free or reduced error capture of symbol images. This results in faster and efficient decoding of symbols. Additional advantages of the workflow will become apparent from the following disclosure.

[0141] Some or all of the steps of process 1000 may be performed by appropriate data processing devices and control devices. For example, in some exemplary embodiments, process 1000 may be performed by a controller or one or more processors of a symbol reader. In some exemplary embodiments, the controller of the symbol reader may be embodied in a manner similar to that described with reference to controller 20 of imaging system 10.

[0142] The process 1000 is triggered upon receiving input from a user to the activation component 206 of the imaging device 200. In response, the process 1000 begins at 1002 by opening a sight as an indicator. Figure 2 As described, the aimer illumination source 110 and the aimer projection optical device 112 can together produce an aimer as a desired pattern. In some exemplary embodiments, the aimer is projected onto the scene by the aimer projection optical device. Next, at 1004, the process 1000 includes capturing a first image of the scene including a mark as an object. The first image can be captured by a near-field image sensor with the aimer turned on. Therefore, the first image can also be referred to as a near-field image. In some exemplary embodiments, the near-field image can be preferably captured with the near-field illumination turned off. However, if the ambient lighting may not be sufficient to capture the near-field image, the near-field image sensor can capture the near-field image with the near-field illumination turned on.

[0143] At 1006, an intensity difference between the projected aiming device and the background is determined. The intensity difference can be determined in a variety of ways, such as by using a previously referenced Figure 8The manner discussed. At 1008, a check of the determined intensity difference is performed. The check determines whether the determined intensity difference is greater than or equal to a threshold value. At 1008, if the result of the check indicates "yes", control passes to 1010, at which the first mode is selected as the distance determination mode. However, if the result of the check at 1008 indicates "no", control passes to 1012, at which the second mode is selected as the distance determination mode. The first mode corresponds to a sequence of steps for determining the distance to an object (such as a marker) based on the distance of the projected sight as captured in the near-field image. The second mode corresponds to a sequence of steps for determining the distance to an object (such as a marker) based on the position of the object in the near-field image and the far-field image captured by the far-field image sensor.

[0144] After selecting a suitable distance determination mode, process 1000 includes calculating the distance to the marker based on the selected distance determination mode at 1014. Figure 8 At step 812 or 814, the distance to the marker may be calculated in accordance with the selected mode. The calculated distance is a measure of the distance of the marker from the imaging engine. Thus, at 1016, process 1000 includes moving the imaging engine in the far field to a focus position determined based on the calculated distance to the marker. As previously described with reference to Figure 8 As discussed in step 816 of , the corresponding focus position of the far-field image sensor can be determined based on the calculated distance to the mark, and the imaging optics of the far-field image sensor of the imaging engine can be moved according to the determined focus position / focus step size. This ensures that the mark is in focus with the far-field image sensor.

[0145] At 1018, an image of the in-focus tag is captured by the far-field image sensor from the set focus position. The image may be referred to as a far-field image of the tag. Process 1000 includes, at 1020, decoding the captured far-field image of the tag to extract information encoded in the tag. The decoded result may be output by the tag reader for subsequent operation or processing.

[0146] In this manner, the exemplary workflow shown in FIG. 10 can be used to perform symbol / sign decoding with appropriate hardware, whereby the likelihood of successfully decoding a target symbol from a near-field image and / or a far-field image is significantly increased due to the improved focus selection control provided by the selected distance determination mode. Such improvements in the decoding process result in improvements in the overall functionality of the symbol decoder device itself.

[0147] Although the exemplary workflow shown in FIG. 10 has been described with reference to the terminal application as symbol decoding, it is contemplated that other terminal application tasks utilizing dual or multiple image sensors (and thereby multiple illumination sources) may also be modified within the scope of the present disclosure to benefit from the improved illumination control and synchronization framework provided herein. That is, the scope of the present disclosure should never be limited to a single symbol decoder, and appropriate modifications may be made to extend the illumination control framework to similar terminal use cases, such as mobile phones based on multiple cameras. In some exemplary contexts, a multi-image sensor device may be embodied as a smartphone having at least two cameras. The camera may have the same or separate illumination sources associated with each of them. At least one camera in a smartphone may be considered a main camera, which is associated with image capture in bright, well-lit and poorly lit situations. The image quality of such a camera may be directly associated with megapixel (MP) intensity, and thus in some exemplary embodiments, the main camera may have 12, 24, 48 or 64 MP. One or more other cameras in a smartphone may be considered as auxiliary cameras associated with one or more image enhancement functions. For example, a smartphone may have a telephoto lens that supports a super zoom option. In some exemplary embodiments, the telephoto lens may support a zoom factor between 2x and 10x. In some more advanced embodiments, the smartphone may have an ultra-wide angle lens for enhancing the field of view of the smartphone. Additionally or optionally, in some exemplary embodiments, the smartphone may include a depth sensor to measure the depth of background objects compared to the main object in the field of view. The smartphone may be equipped with a memory that stores programming instructions corresponding to the logic shown in methods 700, 800, and 1000. These programming instructions can be executed by a processor of the smartphone to perform automatic focus selection during image capture of an object. Since the exemplary embodiments also provide an adaptive process for focus selection, the proposed solution is applicable to various imaging situations and situations.

[0148] It should be understood that the above Figure 7 , Figure 8 and Fig.10Each box in the flowchart shown in and the combination of boxes in the flowchart can be implemented by various devices (such as hardware, firmware, processor, circuit, and / or other communication devices associated with the execution of software including one or more computer program instructions). For example, one or more of the above processes can be embodied by computer program instructions. In this regard, the computer program instructions embodying the above process can be stored by the memory device of the device using the embodiment of the present invention and executed by the processor of the imaging device / system. It should be understood that any such computer program instructions can be loaded onto a computer or other programmable device (e.g., hardware) to produce a machine so that the resulting computer or other programmable device implements the functions specified in the flowchart box. These computer program instructions can also be stored in a computer-readable memory, which can instruct a computer or other programmable device to work in a specific manner so that the instructions stored in the computer-readable memory produce a product, and the execution of these instructions implements the functions specified in the flowchart box. The computer program instructions can also be loaded onto a computer or other programmable device so that a series of operations are performed on the computer or other programmable device, thereby generating a computer-implemented process so that the instructions executed on the computer or other programmable device provide operations for implementing the functions specified in the flowchart box.

[0149] Therefore, the blocks in the flowchart support a combination of means for performing the specified functions and a combination of operations for performing the specified functions / operations. It will also be understood that one or more blocks in the flowchart and a combination of blocks in the flowchart can be implemented by a hardware-based special-purpose computer system that performs the specified functions or a combination of special-purpose hardware and computer instructions.

[0150] Although an exemplary processing system has been described above, specific implementations of the subject matter and functional operations described herein may be implemented in other types of digital electronic circuitry, or in computer software, firmware, or hardware (including the structures disclosed in this specification and their structural equivalents), or in a combination of one or more of them.

[0151] The embodiments of the subject matter and operations described herein may be implemented in digital electronic circuits, or in computer software, firmware or hardware (including the structures disclosed in this specification and their structural equivalents), or in a combination of one or more of them. The embodiments of the subject matter described herein may be implemented as one or more computer programs (i.e., one or more modules of computer program instructions) encoded on a computer storage medium for execution by an information / data processing device or for controlling the operation of an information / data processing device. Alternatively or additionally, program instructions may be encoded on an artificially generated propagation signal (e.g., a machine-generated electrical signal, optical signal, or electromagnetic signal), which is generated to encode information / data for transmission to a suitable receiver device for execution by an information / data processing device. The computer storage medium may be a computer-readable storage device, a computer-readable storage substrate, a random or serial access memory array or device, or a combination of one or more of them, or may be included in a computer-readable storage device, a computer-readable storage substrate, a random or serial access memory array or device, or a combination of one or more of them. Additionally, while a computer storage medium is not a propagated signal, a computer storage medium can be a source or destination of computer program instructions encoded in an artificially generated propagated signal. A computer storage medium can also be, or be included in, one or more separate physical components or media (e.g., multiple CDs, disks, or other storage devices).

[0152] The operations described herein may be implemented as operations performed by an information / data processing apparatus on information / data stored on one or more computer-readable storage devices or received from other sources.

[0153] The term "data processing apparatus" encompasses all kinds of apparatus, devices and machines for processing data, including, for example, a programmable processor, a computer, a system on a chip, or a plurality of the foregoing or a combination thereof. The apparatus may include dedicated logic circuits (e.g., an FPGA (field programmable gate array) or an ASIC (application-specific integrated circuit)). In addition to hardware, the apparatus may also include code that creates an execution environment for the computer program under consideration (e.g., code constituting processor firmware, a protocol stack, a repository management system, an operating system, a cross-platform operating environment, a visual machine, or a combination of one or more of them). The apparatus and execution environment may implement various computing model infrastructures, such as web services, distributed computing infrastructures, and grid computing infrastructures.

[0154] A computer program (also referred to as a program, software, software application, script, or code) may be written in any form of programming language, including compiled or interpreted languages, declarative languages, or procedural languages, and may be deployed in any form, including as a stand-alone program or as a module, component, subroutine, object, or other unit suitable for use in a computing environment. A computer program may, but need not, correspond to a file in a file system. A program may be stored in a portion of a file that holds other programs or information / data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files storing portions of one or more modules, subroutines, or code).

[0155] The processes and logic flows described herein can be performed by one or more programmable processors executing one or more computer programs to perform actions by operating on input information / data and generating output. By way of example, processors suitable for executing computer programs include both general-purpose microprocessors and special-purpose microprocessors and any one or more processors of any kind of digital computer. Generally speaking, the processor will receive instructions and information / data from a read-only memory or a random access memory or both. The basic elements of a computer are a processor for performing actions according to instructions and one or more memories for storing instructions and data. Generally speaking, a computer will also include one or more mass storage devices (e.g., disks, magneto-optical disks, or optical disks) for storing data, or be operably coupled to the one or more mass storage devices to receive information / data from the one or more mass storage devices or transfer information / data to the one or more mass storage devices, or both. However, a computer does not need to have such devices. Devices suitable for storing computer program instructions and information / data include all forms of non-volatile memory, media, and storage devices, including by way of example semiconductor memory devices such as EPROM, EEPROM, and flash memory devices; magnetic disks, such as internal hard disks or removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. The processor and memory may be supplemented by, or incorporated in, special purpose logic circuitry.

[0156] To provide interaction with a user, embodiments of the subject matter described herein may be implemented on a computer having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information / data to the user, as well as a keyboard and pointing device (e.g., a mouse or trackball through which the user can provide input to the computer). Other types of devices may also be used to provide interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including sound, voice, or tactile input. In addition, a computer may interact with a user by sending documents to and receiving documents from a device used by the user; for example, by sending a web page to a web browser in response to a request received from a web browser on a user's client device.

[0157] Although this specification includes many specific implementation details, these details should not be interpreted as limiting the scope of any disclosed or claimable content, but should be interpreted as a description of specific features for a specific disclosed specific embodiment. Certain features described herein in the context of a separate embodiment may also be implemented in combination in a single embodiment. On the contrary, the various features described in the context of a single embodiment may also be implemented in multiple embodiments or in any suitable sub-combination. In addition, although features may be described above as acting in certain combinations and even initially claimed, in some cases, one or more features from the claimed combination may be removed from the combination, and the claimed combination may be for a sub-combination or a variation of the sub-combination.

[0158] Similarly, although operations are depicted in a particular order in the accompanying drawings, this should not be understood as requiring that such operations be performed in the particular order shown or in a sequential order, or that all of the illustrated operations be performed to achieve the desired result. In some cases, multitasking and parallel processing may be advantageous. In addition, the separation of various system components in the above-described embodiments should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or grouped into multiple software products.

[0159] Thus, specific embodiments of the subject matter have been described. Other embodiments are within the scope of the following claims. In some cases, the actions described in the claims can be performed in a different order and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In some specific implementations, multitasking and parallel processing may be advantageous.

Claims

1. A method for imaging using multiple image sensors, the method comprising: capturing, by a first image sensor, a first image of a visual object having a background associated with an object, the visual object being a projected pattern or object projected into a scene to aid in image capture, the object being one or more regions of interest in an imaged scene; Determining a characteristic difference between the visual object in the first image and the background in the first image, wherein determining the characteristic difference comprises at least one of: (i) determining an intensity difference between a first intensity of pixels constituting the visual object in the first image and a second intensity of pixels constituting the background in the first image, and (ii) determining a difference between a sharpness of the visual object in the first image and a sharpness of the background in the first image; selecting a distance determination mode from the first mode and the second mode based on the determined characteristic difference; calculating a distance to the object based on the selected distance determination mode; as well as Based on the calculated distance to the object, a focus position of the second image sensor is changed to capture a second image of the object.

2. The method of claim 1 , wherein selecting a distance determination mode comprises: In response to the intensity difference being greater than or equal to a threshold, selecting the first mode as the distance determination mode; and In response to the intensity difference being less than the threshold, the second mode is selected as the distance determination mode. 3 . The method of claim 2 , wherein the first mode comprises calculating the depth of the visual object in the first image as the distance to the object.

4. The method according to claim 2, wherein the second mode comprises: determining a first position of the object in the first image; capturing a third image of the object by the second image sensor; determining a second position of the object in the third image; as well as A distance to the object is calculated based on the first position and the second position. 5 . The method of claim 4 , wherein the second mode further comprises calculating the distance to the object based on imaging distances of the first image sensor and the second image sensor.

6. The method of claim 4, wherein calculating the distance to the object based on the first position and the second position comprises: calculating a first image offset of the first image based on the first position; calculating a second image offset of the third image based on the second position; as well as The distance to the object is calculated based on the first image offset and the second image offset.

7. The method according to claim 1, further comprising: capturing, by the second image sensor, a second image of the object from the changed focus position; as well as The second image is decoded to extract information encoded in the object.

8. The method according to claim 4, wherein The visual object is a crosshair projection, The object includes an information tag, The first image sensor comprises a near field image sensor, and The second image sensor comprises a far-field image sensor.

9. The method of claim 1, wherein the first image is acquired using a first illumination source configured to illuminate a first field of view that can be captured by the first image sensor.

10. The method of claim 1, wherein the second image is captured using a second illumination source configured to illuminate a second field of view that can be captured by the second image sensor.

11. A system for imaging using multiple image sensors, comprising: a memory configured to store executable instructions; and one or more processors configured to execute the executable instructions to: obtaining, from a first image sensor, a first image of a visual object having a background associated with an object, the visual object being a projected pattern or object projected into a scene to aid in image capture, the object being one or more regions of interest in the imaged scene; Determining a characteristic difference between the visual object in the first image and the background in the first image, wherein determining the characteristic difference comprises at least one of: (i) determining an intensity difference between a first intensity of pixels constituting the visual object in the first image and a second intensity of pixels constituting the background in the first image, and (ii) determining a difference between a sharpness of the visual object in the first image and a sharpness of the background in the first image; selecting a distance determination mode from the first mode and the second mode based on the determined characteristic difference; calculating a distance to the object based on the selected distance determination mode; and Based on the calculated distance to the object, a focus position of the second image sensor is changed to capture a second image of the object.

12. An imaging device, comprising: a first image sensor configured to capture a first image of a visual object having a background associated with an object, the visual object being a projected pattern or object projected into a scene to aid in image capture, the object being one or more regions of interest in an imaged scene; a second image sensor; and A controller, the controller being configured to: obtaining the first image from the first image sensor; Determining a characteristic difference between the visual object in the first image and the background in the first image, wherein determining the characteristic difference comprises at least one of: (i) determining an intensity difference between a first intensity of pixels constituting the visual object in the first image and a second intensity of pixels constituting the background in the first image, and (ii) determining a difference between a sharpness of the visual object in the first image and a sharpness of the background in the first image; selecting a distance determination mode from the first mode and the second mode based on the determined characteristic difference; calculating a distance to the object based on the selected distance determination mode; as well as Based on the calculated distance, a focus position of the second image sensor is changed to capture a second image of the object.

13. A method for imaging using a plurality of image sensors, comprising: capturing, by a first image sensor, a first image of a visual object having a background associated with an object, the visual object being a projected pattern or object projected into a scene to aid in image capture, the object being one or more regions of interest in an imaged scene; capturing, by a second image sensor, a second image of the visual object with a background associated with the object; generating, by a processor, a stereoscopic image based on the first image and the second image; Determining a characteristic difference in the stereoscopic image, wherein determining the characteristic difference comprises at least one of: (i) determining an intensity difference between a first intensity of pixels constituting a visual object in the first image and a second intensity of pixels constituting a background in the first image, and (ii) determining a difference between a sharpness of the visual object in the first image and a sharpness of the background in the first image; and calculating a distance to the object based on the characteristic difference; and Based on the calculated distance to the object, a focus position of at least one of the first image sensor and the second image sensor is changed.

14. The method of claim 13, wherein the characteristic difference corresponds to a level difference in object features of the first image and the second image.

15. The method of claim 13, further comprising using a triangulation distance determination mode to calculate the distance to the object.

16. A system for imaging using a plurality of image sensors, comprising: a memory configured to store executable instructions; and One or more processors configured to execute the executable instructions to: obtaining from a first image sensor a first image of a visual object having a background associated with an object, the visual object being a projected pattern or object projected into a scene to aid in image capture, the object being one or more regions of interest in the imaged scene; obtaining, from a second image sensor, a second image of the visual object with a background associated with the object; generating a stereoscopic image based on the first image and the second image; determining a characteristic difference in the stereoscopic image, wherein determining the characteristic difference comprises at least one of: (i) determining an intensity difference between a first intensity of pixels constituting a visual object in the first image and a second intensity of pixels constituting a background in the first image, and (ii) determining a difference between a sharpness of the visual object in the first image and a sharpness of the background in the first image; calculating a distance to the object based on the characteristic difference; as well as Based on the calculated distance to the object, a focus position of at least one of the first image sensor and the second image sensor is changed.

17. An imaging device comprising: a first image sensor configured to capture a first image of a visual object having a background associated with an object, the visual object being a projected pattern or object projected into a scene to aid in image capture, the object being one or more regions of interest in an imaged scene; a second image sensor configured to capture a second image of the visual object with a background associated with the object; as well as The controller is configured as: acquiring the first image from the first image sensor; acquiring the second image from the second image sensor; generating a stereoscopic image based on the first image and the second image; determining a characteristic difference in the stereoscopic image, wherein determining the characteristic difference comprises at least one of: (i) determining an intensity difference between a first intensity of pixels constituting a visual object in the first image and a second intensity of pixels constituting a background in the first image, and (ii) determining a difference between a sharpness of the visual object in the first image and a sharpness of the background in the first image; calculating a distance to the object based on the characteristic difference; as well as Based on the calculated distance to the object, a focus position of at least one of the first image sensor and the second image sensor is changed.

18. A method for imaging using a plurality of image sensors, comprising: capturing, by a first image sensor, a first image of a visual object having a background associated with an object, the visual object being a projected pattern or object projected into a scene to facilitate image capture, the object being one or more regions of interest in an imaged scene, wherein the first image is captured using a first illumination source configured to illuminate a first field of view that can be captured by the first image sensor; Determining a characteristic difference between the visual object in the first image and the background in the first image, wherein determining the characteristic difference comprises at least one of: (i) determining an intensity difference between a first intensity of pixels constituting the visual object in the first image and a second intensity of pixels constituting the background in the first image, and (ii) determining a difference between a sharpness of the visual object in the first image and a sharpness of the background in the first image; selecting a distance determination mode from the first mode and the second mode based on the determined characteristic difference; calculating a distance to the object based on the selected distance determination mode; as well as Based on the calculated distance to the object, a focus position of a second image sensor is changed to capture a second image of the object, wherein the second image is captured using a second illumination source, the second illumination source being configured to illuminate a second field of view that can be captured by the second image sensor, and wherein the second illumination source is activated between illumination pulses of the first illumination source.

19. A system for imaging using multiple image sensors, comprising: a memory configured to store executable instructions; and One or more processors configured to execute the executable instructions to: obtaining, from a first image sensor, a first image of a visual object having a background associated with an object, the visual object being a projected pattern or object projected into a scene to facilitate image capture, the object being one or more regions of interest in an imaged scene, wherein the first image is obtained using a first illumination source configured to illuminate a first field of view capable of being captured by the first image sensor; Determining a characteristic difference between the visual object in the first image and the background in the first image, wherein determining the characteristic difference comprises at least one of: (i) determining an intensity difference between a first intensity of pixels constituting the visual object in the first image and a second intensity of pixels constituting the background in the first image, and (ii) determining a difference between a sharpness of the visual object in the first image and a sharpness of the background in the first image; selecting a distance determination mode from the first mode and the second mode based on the determined characteristic difference; calculating a distance to the object based on the selected distance determination mode; as well as Based on the calculated distance to the object, a focus position of a second image sensor is changed to capture a second image of the object, wherein the second image is captured using a second illumination source, the second illumination source being configured to illuminate a second field of view that can be captured by the second image sensor, and wherein the second illumination source is activated between illumination pulses of the first illumination source.

20. An imaging device comprising: a first image sensor configured to capture a first image of a visual object having a background associated with an object, the visual object being a projected pattern or object projected into a scene to aid in image capture, the object being one or more regions of interest in an imaged scene; a second image sensor; and A controller, the controller being configured to: obtaining the first image from the first image sensor, wherein the first image is captured using a first illumination source configured to illuminate a first field of view capable of being captured by the first image sensor; Determining a characteristic difference between the visual object in the first image and the background in the first image, wherein determining the characteristic difference comprises at least one of: (i) determining an intensity difference between a first intensity of pixels constituting the visual object in the first image and a second intensity of pixels constituting the background in the first image, and (ii) determining a difference between a sharpness of the visual object in the first image and a sharpness of the background in the first image; selecting a distance determination mode from the first mode and the second mode based on the determined characteristic difference; calculating a distance to the object based on the selected distance determination mode; as well as Based on the calculated distance, a focus position of the second image sensor is changed to capture a second image of the object, wherein the second image is captured using a second illumination source, the second illumination source being configured to illuminate a second field of view that can be captured by the second image sensor, and wherein the second illumination source is activated between illumination pulses of the first illumination source.

Images