Projection obstacle avoidance method and projection system

Abstract

This invention proposes a projection obstacle avoidance method and projection system. The projection obstacle avoidance method includes: acquiring a reference image, wherein the reference image includes a correction image; receiving reference image information and obtaining correction image information; calculating multiple matching image feature point pairs based on the reference image information and the correction image information; mapping and transforming the region information corresponding to the correction image in the reference image information based on the multiple matching image feature point pairs to generate obstacle avoidance image information; performing edge detection operations on the obstacle avoidance image information to generate edge detection result image information, and correcting the partial information in the edge detection result image information corresponding to the correction pattern; and performing region judgment operations on the corrected edge detection result image information to set a maximum obstacle-free area in the edge detection result image.

Description

Technical Field

[0001] This invention relates to a projection correction technique, and more particularly to a projection obstacle avoidance method and projection system. Background Technology

[0002] With the widespread adoption of multimedia applications, projectors have become widely used in various scenarios such as education, business presentations, home entertainment, and outdoor displays. Traditional projectors often require a projection screen or a flat wall surface to achieve the desired display effect. However, when projectors operate in less than ideal environments, such as confined spaces, spaces with many objects, or asymmetrical structures, the projected image is easily obstructed or interfered with by environmental obstacles, resulting in incomplete image presentation and negatively impacting the user experience.

[0003] Most projectors in the current technology do not have automatic obstacle avoidance projection functions. Especially in the absence of image sensing devices (such as camera modules), when an obstacle appears in the projection area and partially obstructs the projected image, manual adjustments to the projector's placement, angle, or projection area size are necessary to prevent the image from being projected onto the obstacle and ensure a smooth viewing experience. This manual adjustment method is not only time-consuming and laborious but also requires users to have a certain understanding of projection principles, posing a barrier to entry for the average consumer.

[0004] The "Background Art" paragraph is only used to help understand the content of this invention. Therefore, the content disclosed in the "Background Art" paragraph may include some known technologies that are not known to those skilled in the art. The content disclosed in the "Background Art" paragraph does not mean that the content or the problems to be solved by one or more embodiments of this invention were known or understood by those skilled in the art prior to this application. Summary of the Invention

[0005] In view of this, the present invention provides a projection obstacle avoidance method and projection system, which can be used to solve the above-mentioned technical problems.

[0006] Other objects and advantages of the present invention can be further understood from the technical features disclosed herein.

[0007] To achieve one or more of the above objectives or other objectives, one embodiment of the present invention provides a projection obstacle avoidance method performed by a mobile device, the mobile device including a camera unit and a processing unit coupled to the camera unit, the mobile device being communicatively connected to a projection device. The projection obstacle avoidance method includes: capturing a first reference image by the camera unit, wherein the first reference image includes a first corrected image projected onto a projection surface by the projection device according to first corrected image information, and the first corrected image includes a correction pattern; and performing the following steps by the processing unit: receiving first reference image information corresponding to the first reference image from the camera unit, and obtaining first corrected image information corresponding to the first corrected image; calculating a plurality of matching image feature point pairs based on the first reference image information and the first corrected image information; mapping and transforming the region information in the first reference image information corresponding to the first corrected image based on the plurality of matching image feature point pairs to generate obstacle avoidance image information; performing edge detection operation on the obstacle avoidance image information to generate edge detection result image information corresponding to the edge detection result image, and correcting part of the information in the edge detection result image information corresponding to the correction pattern; performing region judgment operation on the corrected edge detection result image information to set a maximum obstacle-free area in the edge detection result image; and generating a plurality of projection range coordinates based on the maximum obstacle-free area, and sending the plurality of projection range coordinates to the projection device.

[0008] To achieve one or more of the above objectives or other objectives, one embodiment of the present invention provides a projection obstacle avoidance method performed by a mobile device, the mobile device including a camera unit and a processing unit coupled to the camera unit, the mobile device being communicatively connected to a projection device. The projection obstacle avoidance method includes: capturing a first reference image by the camera unit, wherein the first reference image includes a first corrected image projected onto a projection surface by the projection device, the first corrected image including a correction pattern; capturing a second reference image by the camera unit, wherein the second reference image includes a second corrected image projected onto the projection surface by the projection device, the second corrected image being a background color image; and performing the following steps by the processing unit: receiving first reference image information corresponding to the first reference image and second reference image information corresponding to the second reference image from the camera unit, and obtaining first corrected image information corresponding to the first corrected image; calculating multiple matching image feature point pairs based on the first reference image information and the first corrected image information; mapping and transforming the region information corresponding to the first corrected image in the second reference image information based on the multiple matching image feature point pairs to generate obstacle avoidance image information; performing edge detection operation on the obstacle avoidance image information to generate edge detection result image information corresponding to the edge detection result image; performing region judgment operation on the edge detection result image information to set an optimal obstacle-free region in the edge detection result image; and generating multiple projection range coordinates based on the maximum obstacle-free region, and sending the multiple projection range coordinates to the projection device.

[0009] To achieve one, some, or all of the above-mentioned objectives, or other objectives, one embodiment of the present invention provides a projection system including a projection device and a mobile device. The projection device projects a first corrected image onto a projection surface based on first corrected image information, the first corrected image including a corrected pattern. The mobile device is communicatively connected to the projection device and configured to perform the projection obstacle avoidance method as described above. The projection device sets a projection range based on the plurality of projection range coordinates.

[0010] In summary, the projection obstacle avoidance method and projection system of the present invention can achieve automatic obstacle recognition of the projection device through a mobile device, and provide a convenient operating interface through a mobile device application, enabling the projection system to automatically correct and adjust the projection area without requiring the user to manually set or adjust the projection device. The automatic obstacle avoidance mechanism described in this invention can quickly complete the setting of the maximum usable projection range, greatly simplifying the setup process and improving overall accuracy.

[0011] To achieve one, some, or all of the above-mentioned objectives, or other objectives, one embodiment of the present invention provides a projection system including a projection device and a mobile device. The projection device projects a first corrected image onto a projection surface based on first corrected image information, and projects a second corrected image onto the projection surface based on second corrected image information, wherein the first corrected image includes a correction pattern, and the second corrected image is a background color image. The mobile device is communicatively connected to the projection device and configured to perform the projection obstacle avoidance method described above. The projection device sets a projection range based on the plurality of projection range coordinates. Attached Figure Description

[0012] Figure 1 This is a block diagram of the projection system of the present invention.

[0013] Figure 2 This is a flowchart of the projection obstacle avoidance method according to the first embodiment of the present invention.

[0014] Figure 3A This is a schematic diagram of the first corrected image according to the first embodiment of the present invention.

[0015] Figure 3B This is a schematic diagram of a preview screen of a mobile device according to the first embodiment of the present invention.

[0016] Figure 4A It is the original first reference image captured by the camera unit of the mobile device in the first embodiment of the present invention.

[0017] Figure 4B This is the first reference image after preprocessing in the first embodiment of the present invention.

[0018] Figure 4C This is a schematic diagram of the matching of the first corrected image and the first reference image for image feature matching in the first embodiment of the present invention.

[0019] Figure 4D It is the image region in the first reference image after mapping and transformation, corresponding to the first corrected image, in the first embodiment of the present invention.

[0020] Figure 4E It is Figure 4D The obstacle avoidance image is generated after the image area is mapped and transformed by another method.

[0021] Figure 4F It is Figure 4E The edge detection result image is generated after edge detection calculation is performed on the obstacle avoidance image.

[0022] Figure 4G It is Figure 4E The edge detection result image after region masking.

[0023] Figure 5A and Figure 5B This is a flowchart of the process of performing region judgment calculation on the image information of the edge detection result in the first embodiment of the present invention.

[0024] Figure 6A and 6B This is a schematic diagram illustrating the application of the flowchart for the region judgment operation in the first embodiment of the present invention.

[0025] Figure 7A and 7B This is another application diagram of the flowchart for the region judgment operation in the first embodiment of the present invention.

[0026] Figure 8 This is a schematic diagram of the maximum barrier-free area in the first embodiment of the present invention.

[0027] Figure 9 This is a flowchart of the projection obstacle avoidance method according to the second embodiment of the present invention.

[0028] Figure 10A It is the original first reference image captured by the camera unit of the mobile device in the second embodiment of the present invention.

[0029] Figure 10B This is the first reference image after preprocessing in the second embodiment of the present invention.

[0030] Figure 11A It is the original second reference image captured by the camera unit of the mobile device in the second embodiment of the present invention.

[0031] Figure 11B This is the second reference image after preprocessing in the second embodiment of the present invention.

[0032] Figure 11C It is the image region in the second reference image after mapping and transformation in the second embodiment of the present invention that corresponds to the first corrected image.

[0033] Figure 11D It is Figure 11C The obstacle avoidance image is generated after the image area is mapped and transformed by another method.

[0034] Explanation of reference numerals in the attached figures:

[0035] 100: Projection System

[0036] 110: Mobile devices

[0037] 120: Projection device

[0038] 111: Camera Unit

[0039] 112: First storage unit

[0040] 113: First Processing Unit

[0041] 114: First Communication Unit

[0042] 115: Display Unit

[0043] 121: Second Communication Unit

[0044] 122: Second storage unit

[0045] 123: Second Processing Unit

[0046] 124: Image Processing Unit

[0047] 125: Lighting System

[0048] 126: Optical Modulation Module

[0049] 127: Projection Lens

[0050] 112a, 122a: Applications

[0051] S210-S270, S511-S522, S910-S970: Step 310: First Corrected Image

[0052] 311: Correction Pattern

[0053] 320: User Interface

[0054] 330, 412: First reference image

[0055] 340,499: Obstacles

[0056] 411: First Reference Image

[0057] 420: Connection

[0058] 430,1110: Image area

[0059] 440, 1120: Obstacle Avoidance Images

[0060] 450, 460: Edge detection result image

[0061] 499a: Obstacle edge

[0062] 451: Masked Area

[0063] 452: Mask

[0064] 610, 611-614, 621, 711-714, 721, 722, 811: Candidate image regions

[0065] W11, W12, W18: Width

[0066] H11, H12, H18: Height

[0067] D1: First Direction

[0068] D2: Second Direction

[0069] 1011: First Reference Image

[0070] 1012: Second Reference Image

[0071] Xstep: First movement range

[0072] Ystep: Second movement amplitude

[0073] A11,A12,A21,An,B11,B12,B21,Bn,C11,C12,C21,Cn,D11,D12,D21,Dn: Coordinates. Detailed Implementation

[0074] The foregoing descriptions and other technical contents, features, and effects of this invention will be clearly presented in the following detailed description of a preferred embodiment with reference to the accompanying drawings. The directional terms used in the following embodiments, such as up, down, left, right, front, or back, are merely for reference to the accompanying drawings. Therefore, the directional terms used are for illustrative purposes and not for limiting the invention.

[0075] Please refer to Figure 1 , Figure 1 This is a block diagram of a projection system drawn according to a first embodiment of the present invention. Figure 1 In the projection system 100, there are a mobile device 110 and a projection device 120. The mobile device 110 and the projection device 120 are connected via wired / wireless means and work together to perform projection obstacle avoidance function to automatically adjust the projection range.

[0076] In the first embodiment, the mobile device 110 includes a camera unit 111 and a first processing unit 113 coupled to the camera unit 111. The camera unit 111 captures a first reference image, wherein the first reference image includes a first correction image projected onto a projection surface by a projection device 120 according to first correction image information, and the first correction image includes a correction pattern. The first processing unit 113 of the mobile device 110 is configured to perform the following steps: receive first reference image information corresponding to the first reference image 330 from the camera unit 111, and obtain first correction image information corresponding to the first correction image 310; calculate multiple matching image features based on the first reference image information and the first correction image information; based on the multiple matching image features, perform mapping transformation on the region information in the first reference image information corresponding to the first correction image to generate obstacle avoidance image information; perform edge detection operation on the obstacle avoidance image information to generate edge detection result image information corresponding to the edge detection result image, and correct the part of the edge detection result image information corresponding to the correction pattern; perform region judgment operation on the corrected edge detection result image information to set a maximum barrier-free area in the edge detection result image; and generate multiple projection range coordinates based on the large barrier-free area, and send the multiple projection range coordinates to the projection device 120.

[0077] In the first embodiment, the mobile device 110 may further include a first storage unit 112, a first communication unit 114 and a display unit 115, wherein the first processing unit 113 is coupled to the first storage unit 112, the first communication unit 114 and the display unit 115.

[0078] The projection device 120 includes a second communication unit 121, a second storage unit 122, a second processing unit 123, an image processing unit 124, an illumination system 125, a light modulation module 126, and a projection lens 127. The second processing unit 123 is coupled to the second communication unit 121, the second storage unit 122, and the image processing unit 124. The light modulation module 126 is coupled to the image processing unit 124, the illumination system 125, and the projection lens 127.

[0079] The first storage unit 112 of the mobile device 110 stores the application 112a and the first correction image information of the first correction image. When the first processing unit 113 of the mobile device 110 executes the application 112a, it can be used to manage and operate the projection device 120, exchange information with the projection device 120, and / or present the corresponding operation interface on the display unit 115. The operation interface may display, for example, the identity information of the projection device 120 (such as the brand name, model, number, etc. of the projection device 120).

[0080] Furthermore, the first corrected image is applied to the projection obstacle avoidance method proposed in this invention, and related details will be explained in subsequent embodiments.

[0081] In this embodiment of the invention, the term "image information of a certain image" can broadly refer to information related to the image extracted, analyzed, or derived from it, including but not limited to geometric information and content information. In one embodiment, the aforementioned geometric information may include the spatial location (e.g., coordinates), size (e.g., length / width, area), shape (e.g., rectangle, circle), orientation (e.g., rotation angle), or relative positional relationship with other objects of a pattern or specific target in the image. This type of information can be used to describe the spatial distribution characteristics of a pattern or specific target in the image, or to calculate the correspondence between the image and the physical environment. Furthermore, the aforementioned content information refers to pixel values ​​(e.g., brightness, color, grayscale values), texture features (e.g., edges, corners, pattern variations), and pattern structures (e.g., line distribution, block segmentation results) contained in the image. This type of information can be used to identify patterns, determine image quality, or extract specific areas for subsequent processing.

[0082] Based on this principle, the first corrected image information of the first corrected image may include, for example, geometric information and content information related to the first corrected image, but may not be limited to this.

[0083] When the first processing unit 113 of the mobile device 110 executes the application 112a, the first processing unit 113 displays the operation interface of the application 112a via the display unit 115. The operation interface of the application 112a displayed on the display unit 115 can show a list of all devices within the communication range of the first communication unit 114. The user of the mobile device 110 can select the identity information of the projection device 120 from the list on the operation interface of the application 112a to establish a connection between the mobile device 110 and the projection device 120.

[0084] In response to the selection of the identity information of the projection device 120, the first processing unit 113 controls the first communication unit 114 to establish a connection with the projection device 120. In this case, the first communication unit 114 may, for example, establish a corresponding connection with the second communication unit 121 of the projection device 120 according to the supported communication protocol (e.g., Bluetooth).

[0085] The user interface of application 112a provides obstacle avoidance function options to trigger the mobile device 110 and the projection device 120 to jointly execute the projection obstacle avoidance method proposed in the embodiments of the present invention, and the details of this method will be further explained in subsequent embodiments.

[0086] In one embodiment, in response to the determination that the obstacle avoidance function option in the operation interface of the application 112a is triggered, the first processing unit 113 controls the first communication unit 114 to send an obstacle avoidance function activation command to the selected projection device 120 through the above connection.

[0087] Please continue to refer to this. Figure 1 The second storage unit 122 of the projection device 120 is used to store the application program 122a and the first correction image information corresponding to the first correction image. After the second communication unit 121 of the projection device 120 receives the obstacle avoidance function activation command from the mobile device 110, the second processing unit 123 can execute the application program 122a in response to the obstacle avoidance function activation command. The first correction image information stored in the second storage unit 122 of the projection device 120 is the same as the first correction image information stored in the first storage unit 112 of the mobile device 110.

[0088] The illumination system 125 of the projection device 120 generates an illumination beam, while the image processing unit 124 of the projection device 120 receives first correction image information from the second processing unit 121 and controls the light modulation module 126 to convert the illumination beam into an image beam corresponding to the first correction image based on the first correction image information. The projection lens 127 of the projection device 120 projects the image beam corresponding to the first correction image onto a projection surface.

[0089] After the projection device 120 is powered on, the second processing unit 123 can perform image keystone correction based on the device attitude information of the projection device 120 to generate multiple corrected projection corner coordinates, which serve as projection range indicators of the first corrected image after projection adjustment by the projection device 120. In some embodiments, the device attitude information of the projection device 120 may refer to information describing the orientation and tilt state of the projection device 120 in space, including but not limited to at least one attitude angle among pitch, roll, and yaw. The aforementioned device attitude information can be used to represent the coordinates and / or rotation state of the projection device relative to a reference coordinate system (e.g., the direction of gravity or the normal to the projection surface). In some embodiments, the aforementioned device attitude information can be obtained in real time through a sensing module (e.g., an accelerometer, a gyroscope, and / or a ranging module) built into the projection device 120, but is not limited to this.

[0090] Next, the second processing unit 123 of the projection device 120 can control the second communication unit 121 to send the above-mentioned corrected projection corner coordinates to the mobile device 110 as the basis for subsequent execution of the projection obstacle avoidance method, but it is not limited to this.

[0091] In addition, the second processing unit 123 of the projection device 120 can also generate adjusted first corrected image information based on the above-mentioned corrected projection corner point coordinates, and send the adjusted first corrected image information to the image processing unit 124. Accordingly, the image processing unit 124 can control the light modulation module 126, so that the light modulation module 126 converts the illumination beam into an image beam corresponding to the adjusted first corrected image based on the adjusted first corrected image information, and the image beam corresponding to the adjusted first corrected image is projected by the projection lens 127.

[0092] The image beam can be projected by the projection lens 127 onto a projection surface (e.g., a screen and / or a wall) to form an adjusted first corrected image.

[0093] exist Figure 1 In this context, the mobile device 110 can be a portable electronic device with processing and communication capabilities, such as a smartphone, tablet, laptop, or wearable device with image capture and processing capabilities. It can have various embedded or external sensing circuits and display circuits to provide a user interface and perform image analysis processing.

[0094] The camera unit 111 may be a digital camera circuit, which may be embedded inside the mobile device 110 or externally connected via wired or wireless means. The camera unit 111 may include an image sensor (e.g., a CMOS sensor), a lens module, and related image processing circuitry to capture images of the environment and convert them into digital image data and / or image information.

[0095] The first storage unit 112 may include any type of fixed or removable storage device, such as random access memory (RAM), read-only memory (ROM), flash memory, cache, solid-state drive (SSD), hard drive disk (HDD), memory card, USB flash drive, or any combination thereof.

[0096] The first processing unit 113 may be a logic processor with data processing and control functions, such as a central processing unit (CPU), a digital signal processor (DSP), an application processor (AP), a system-on-chip (SoC), or a combination thereof, to execute functional modules such as image processing analysis and projection obstacle avoidance methods.

[0097] The first communication unit 114 can support wired or wireless data transmission methods, establish a connection with the projection device 120, and transmit relevant information such as the coordinates of the projection area. The data transmission method can include at least one of the following communication protocols: Wi-Fi (IEEE 812.11), Bluetooth, Near Field Communication (NFC), Zigbee, 4G mobile network (including 4G mobile network, 5G mobile network, or other mobile communication standards that comply with ITU recommendations), Universal Serial Bus (USB), Universal Asynchronous Receiver / Transmitter (UART), or Ethernet, etc.

[0098] The display unit 115 can be various display devices, such as a liquid crystal display (LCD), an organic light-emitting diode (OLED) display module, an electronic paper module, or other display devices with graphical user interface functionality, used to display reference images or application operation screens. In some embodiments, the display unit 115 can be integrated with an input interface module, such as integrating with a touch panel to form a touch display module.

[0099] The projection device 120 can be a single, all-in-one projection device or a combination device containing multiple modules, such as a laser projector, a Digital Light Processing (DLP) projector, an LCD projector, or a short-throw laser projection module. It can support fixed or portable installation and has keystone correction and projection area adjustment functions.

[0100] The second communication unit 121 of the projection device 120 may be implemented in a manner that corresponds to or is the same as the first communication unit 114, so as to realize the transmission and reception of data or instructions with the mobile device 110.

[0101] The second storage unit 122 of the projection device 120 is similar in nature to the first storage unit 112, and may also include at least one memory module selected from RAM, ROM, Flash Memory, SSD, and HDD.

[0102] The second processing unit 123 of the projection device 120 may be a main processor that controls the operation of the projection device, or it may be at least one of a SoC, FPGA, microcontroller (MCU), DSP or embedded processor circuit.

[0103] The image processing unit 124 of the projection device 120 can be a dedicated processor for processing image content, used to process and correct image information, adjust the output screen and control the light modulation module 126.

[0104] The lighting system 125 of the projection device 120 includes one or more light source modules, wavelength conversion devices, light splitting and combining modules, and light homogenizing elements. Light source modules may include, for example, laser light sources, LED light sources, xenon lamps, etc., and light splitting and combining modules may include, for example, at least one or a combination of a reflector, a beam splitter, and a beam combiner. In one embodiment, a second processing unit 123 is coupled to the lighting system 125 and is adapted to control the lighting system 125.

[0105] The light modulation module 126 is, for example, a reflective light modulator such as a liquid crystal on silicon panel (LCoSpanel) or a digital micromirror device (DMD). In some embodiments, the light modulation device 2 may also be a transmissive light modulator such as a transparent liquid crystal panel, an electro-optic modulator, a magneto-optic modulator, or an acousto-optic modulator (AOM). This invention does not limit the type or form of the light modulation module 126. The detailed steps and implementation methods of the method by which the light modulation module 126 converts an illumination beam into an image beam are sufficiently taught, suggested, and explained by knowledge of the art, and therefore will not be elaborated further.

[0106] The projection lens 127 can be a fixed-focus or zoom lens module, used to project a modulated image beam onto a predetermined projection surface. The projection lens 127 may also include a focusing mechanism, a lens movement mechanism, or an optical distortion compensation module. The projection lens 127 may include, for example, a combination of one or more optical lenses with refractive power, such as various combinations of non-planar lenses including biconcave lenses, biconvex lenses, concave-convex lenses, convex-concave lenses, plano-convex lenses, and plano-concave lenses. In one embodiment, the projection lens 127 may also include a planar optical lens to reflect the image beam from the light modulation module 126 onto the projection target. This invention does not limit the type or form of the projection lens light modulation module 126.

[0107] Please refer to Figure 2 This is a flowchart illustrating a projection obstacle avoidance method according to a first embodiment of the present invention. The method of this embodiment can be derived from... Figure 1 The mobile device 110 performs the following actions: Figure 1Component description shown Figure 2 Details of each step.

[0108] In step S210, camera unit 111 captures a first reference image, which includes a first corrected image projected onto the projection surface by projection device 120 based on first corrected image information, and this first corrected image includes a correction pattern. Further, the first corrected image projected onto the projection surface by projection device 120 based on first corrected image information may include a first corrected image projected by projection device 120 based on original first corrected image information, and an adjusted first corrected image projected onto the projection surface by projection device 120 based on adjusted first corrected image information. When the second processing unit 123 of projection device 120 does not perform image keystone correction based on the device posture information of projection device 120, projection device 120 projects the first corrected image based on the original first corrected image information.

[0109] Figure 3A This is a schematic diagram of the first corrected image according to the first embodiment of the present invention. Figure 3B This is a schematic preview of the mobile device according to the first embodiment of the present invention.

[0110] After receiving the obstacle avoidance function activation command from the mobile device 110, the projection device 120 projects the first corrected image 310 onto the corresponding projection surface. (Refer to...) Figure 3A The first corrected image 310 includes a corrected pattern 311.

[0111] Please refer to the above as well. Figure 1 , Figure 3A and 3B After the obstacle avoidance function of the application 112a on the mobile device 110 is triggered, the first processing unit 112 correspondingly activates the image capturing function of the camera unit 111, and the display unit 115 displays the image on the application 112a's interface 3 as shown in the image. Figure 3B The preview screen shown. Afterwards, the user of the mobile device 110 can operate the camera unit 111 to take a picture of the first corrected image 310 projected onto the projection surface, and the image captured by the camera unit 111 can be displayed by the display unit 115 in the operation interface 320 of the application 112a so that the user can confirm that the capture was successful.

[0112] exist Figure 3B In this context, the image captured by camera unit 111 can be understood as the first reference image 330 under consideration. Figure 3BAs can be seen, the projection device 120 projects the first corrected image 310 onto the projection surface within a projection range containing an obstacle 340. In this invention, the presence of an obstacle within the projection range is defined as the projected image being at least partially projected onto the obstacle. In other words, if the projection device 120 projects other images onto the projection surface in the current manner, the quality of the projected image will be affected by the obstacle 340.

[0113] exist Figure 3A and Figure 3B In this context, although the correction pattern 311 is illustrated in a form similar to a Quick Response (QR) code, it is merely an example and not intended to limit possible implementations of the invention. In other embodiments, the designer can customize the required correction pattern as needed. Furthermore, in Figure 3A and Figure 3B In this scenario, the correction pattern 311 is located at the center of the first correction image 310. The correction pattern 311 may also be located at other locations within the first correction image 310, such as the edges or corners of the first correction image 310. The user must ensure that the first reference image 330 encompasses the entire first correction image 310.

[0114] Please refer to this again. Figure 2 After capturing the first reference image 310, in step S220, the first processing unit 113 receives the first reference image information corresponding to the first reference image 330 from the camera unit 111, and obtains the first correction image information corresponding to the first correction image 310.

[0115] In some embodiments, the first correction image information may be downloaded in advance via the Internet to an address specified by application 112a and stored in the first storage unit 112. In other embodiments, the first correction image information may also be transmitted from the projection device 120 to the mobile device 110 for storage in the first storage unit 112 when the mobile device 110 and the projection device 120 establish a connection, thereby ensuring that the first correction image information stored on the mobile device 110 and the projection device 120 is the same.

[0116] The following will be further supplemented Figure 4A to Figure 4G The experimental images are used to illustrate this. Figure 4A The original first reference image captured by the camera unit of the mobile device in the first embodiment of the present invention; Figure 4B This is the first reference image after preprocessing by the first processing unit in the first embodiment of the present invention; Figure 4C This is a schematic diagram of the matching of the first corrected image and the first reference image for image feature matching in the first embodiment of the present invention; Figure 4D In the first embodiment of the present invention, the image region in the first reference image after mapping and transformation corresponds to the first corrected image; Figure 4E To beFigure 4D The obstacle avoidance image generated after the image area is mapped and transformed in another way; Figure 4F To be Figure 4E The edge detection result image generated after performing edge detection calculation on the obstacle avoidance image; Figure 4G This is the edge detection result image after region masking in the first embodiment of the present invention.

[0117] Please refer to Figure 4A and 4B In this embodiment, the first processing unit 113 may, for example, preprocess the original first reference image 411 to generate a preprocessed first reference image 412. Further, after the camera unit 111 captures the first reference image 411 in response to a user's trigger, the first processing unit 113 may first perform one or more preprocessing steps on the original first reference image information generated by the camera unit 111 to facilitate subsequent analysis / computation. In different embodiments, the one or more preprocessing steps may include at least one of the following: converting the original image information into grayscale information, using contrast-limited adaptive histogram equalization (CLAHE), or other image processing methods to enhance contrast, but are not limited to these.

[0118] Depend on Figure 4A and Figure 4B It can be seen that the projection range of the projection device 120 currently includes part of the obstacle 499.

[0119] Please refer to Figure 2 In step S230, the first processing unit 113 calculates multiple matching image feature point pairs based on the first reference image information and the first correction image information.

[0120] Please refer to Figure 4C In this image, the left side represents the first corrected image 310, and the right side represents the (preprocessed) first reference image 412. The two ends of each connecting line 420 between the two images are connected to matching image feature point pairs in the first corrected image 310 and the first reference image 412, respectively. Here, the matching image feature points in the first corrected image 310 and the first reference image 412 are referred to as a matching image feature point pair.

[0121] In some embodiments, the first processing unit 113 may further perform a filtering operation on the matching image feature point pairs in the first corrected image 310 and the first reference image 412 to filter out matching image feature point pairs with good matching characteristics.

[0122] In some embodiments, the first processing unit 113 further determines whether the number of matched image feature point pairs found is higher than a preset number threshold. If yes, the first processing unit 113 may continue to perform subsequent operations of the projection obstacle avoidance method; if no, the first processing unit 113 may control the display unit 115 to display the corresponding error message or warning message, and / or return to step S210 to re-capture the first reference image.

[0123] Please refer to this again. Figure 1 and Figure 2 After calculating the plurality of matching feature image feature point pairs in step S230, in step S240, the first processing unit 113 performs mapping and transformation on the region information corresponding to the first correction image 310 in the first reference image information based on the plurality of matching image feature point pairs to generate obstacle avoidance image information.

[0124] In some embodiments, the first processing unit 113 may generate the obstacle avoidance image information based on a perspective transformation method. Specifically, in this embodiment, the first processing unit 113 first generates a first transformation matrix based on the plurality of matching image feature point pairs, mapping the coordinate system of the first corrected image to the coordinate system of the first reference image, and performs an inverse matrix operation on the first transformation matrix to generate a second transformation matrix.

[0125] Next, the first processing unit 113 can use the first transformation matrix to map the first corrected image information to the first reference image information to determine the region information in the first reference image information corresponding to the first corrected image 310.

[0126] In embodiments of the present invention, the regional information of a certain image region may be information describing the spatial geometric attributes and image content features of a specific region in the image, including but not limited to geometric information and content information.

[0127] The geometric information of an image region can refer to the spatial distribution information of this image region in the image coordinate system, such as the boundary coordinates of the region (e.g., the positions of the upper left and lower right corners), the position of the center point, the length and width dimensions, the area size, or its shape type (e.g., rectangle, polygon, or irregular block). In addition, it can also include the position of the region relative to the overall image (e.g., located at the center or corner of the image) and its relative positional relationship with other regions.

[0128] In addition, the content information of an image region can refer to the image features of the pixels in that region, such as pixel brightness values, grayscale values, color distribution (e.g., RGB average or standard deviation), texture features (e.g., edge density, pattern repeatability), or whether the region contains a predetermined target pattern (e.g., a specific mark or structural pattern). This type of information can be calculated and extracted by image processing algorithms and used as the basis for subsequent identification, correction, or control operations.

[0129] Please refer to the above as well. Figure 4D and Figure 4E The region information in the first reference image information corresponding to the first corrected image 310, for example, may correspond to... Figure 4D The image region 430 is extracted from the first reference image. That is, the region information corresponding to the first corrected image 310 may include, for example, geometric information and content information related to the image region 430, but may not be limited to these.

[0130] Next, the first processing unit 113 can use the second transformation matrix to map the area information into obstacle avoidance image information.

[0131] The obstacle avoidance image information may correspond to, for example, [the information related to] the [objective avoidance] image information. Figure 4E The obstacle avoidance image 440 in the image. That is, the obstacle avoidance image information may include, for example, geometric information and content information related to the obstacle avoidance image 440, but is not limited to this.

[0132] Please refer to again Figure 1 and Figure 2 After generating obstacle avoidance image information in step S240, in step S250, the first processing unit 113 performs edge detection operation on the obstacle avoidance image information to generate edge detection result image information corresponding to the edge detection result image, and corrects the part of the edge detection result image information corresponding to the correction pattern 311.

[0133] In embodiments of the present invention, the edge detection result image information refers to the image information generated after performing edge detection processing (e.g., Sobel, Canny, or Laplacian algorithms) on the original obstacle avoidance image information. This image information includes, but is not limited to, edge pixel location information and / or edge intensity information. The edge pixel location information describes the spatial coordinates of pixels in the image that are identified as edges. Furthermore, the edge intensity information refers to the gradient magnitude of edge pixels in the image, reflecting the sharpness or contrast intensity of the edges, and can be used as a basis for filtering weak or noisy edges.

[0134] Please refer to the above as well. Figure 4F The edge detection result image information generated after the obstacle avoidance image information is processed by edge detection can, for example, correspond to edge detection result image 450. Figure 4FIt can be seen that the edge detection result image 450 also includes elements corresponding to... Figure 4B to Figure 4E The obstacle edge 499a of the obstacle 499. In other words, the edge detection result image information still contains edge information related to the obstacle 499.

[0135] Next, refer to Figure 3A The first processing unit 113 can obtain geometric information of the first image region occupied by the correction pattern 311 in the first correction image 311.

[0136] Subsequently, the first processing unit 113 performs region masking on the edge detection result image information based on the geometric information of the first image region, so as to exclude the pattern edge 311a corresponding to the correction pattern 311 in the edge detection result image 450.

[0137] Please refer to Figure 4F and 4G Specifically, the first processing unit 113 first determines the masking region 451 in the edge detection result image 450 based on the geometric information of the first image region, and then applies the masking information to the masking region 451 of the edge detection result image 450, such as... Figure 4G The edge pixels within the masking area 452 are covered (e.g., pixel values ​​are set to zero or marked as ignored areas), forming an edge detection result image 460 corresponding to the corrected edge detection result image information, thereby achieving the purpose of correcting a portion of the information in the edge detection result image information corresponding to the correction pattern 311. Figure 4G It can be seen that the corrected edge detection result image 460 no longer includes some information (e.g., edge information) corresponding to the correction pattern 311.

[0138] By using this masking process, the edges corresponding to the correction pattern 311 in the corrected edge detection result image 460 will not participate in subsequent analysis, thereby effectively eliminating the influence of the correction pattern 311 on subsequent calculations. The corrected edge detection result image 460 only contains the obstacle edges 499a related to the obstacle 499.

[0139] Please refer to this again. Figure 2 In step S260, the first processing unit 113 performs region determination calculations on the corrected edge detection result image information to set the maximum unobstructed area in the corrected edge detection result image 460. Specifically, Figure 2 Step S260 further includes steps S511-S520.

[0140] Figure 5A and Figure 5B This is a flowchart of the region determination operation performed on the image information of the edge detection results in the first embodiment of the present invention. To make... Figure 5Aand Figure 5B The concept is easier to understand; additional information is provided below. Figure 6A and Figure 6B As explained, among them Figure 6A and 6B This is a schematic diagram illustrating the application of the flowchart for the region judgment operation in the first embodiment of the present invention.

[0141] In some embodiments, in the initial stage of the step where the first processing unit 113 performs region determination calculation on the corrected edge detection result image information to set the maximum unobstructed area in the corrected edge detection result image 460, step S510 is performed first. That is, the first processing unit 113 first determines the candidate image region 610 based on the size of the edge detection result image 460. The first processing unit 113 calculates the grayscale parameters of all pixels in the candidate image region 610 corresponding to the corrected edge detection result image information, and determines whether the candidate image region 610 meets the preset conditions based on the grayscale parameters. If yes, the first processing unit 113 can continue to execute step S513; if no, the first processing unit 113 can continue to execute step S511. The steps involve determining the candidate image region based on the size of the edge detection result image, calculating the grayscale parameters of all pixels in the candidate image region corresponding to the corrected edge detection result image information, and determining whether the candidate image region meets the preset conditions based on the grayscale parameters.

[0142] Please refer to Figure 5A In step S511, the first processing unit 113 determines the candidate image region 611 in the edge detection result image 460 according to the preset size.

[0143] exist Figure 6A In this scenario, the preset size, for example, has a width W11 and a height H11, and the ratio between the width W11 and the height H11 can conform to a preset aspect ratio. Furthermore, the preset size is smaller than the size of the edge detection result image 460. Preferably, this preset aspect ratio is the same as the current projection aspect ratio of the projection device 120 (e.g., 16:9). For clarity, the width in the aspect ratio is defined, for example, as the length in the Y-axis direction of the edge detection result image 460, and the height is defined as the length in the X-axis direction of the edge detection result image 460.

[0144] In one embodiment, in the initial stage of the region determination operation, the first processing unit 113 first determines the candidate image region 611 corresponding to the preset size at the initial position in the edge detection result image 460.

[0145] exist Figure 6AIn this context, the initial position is, for example, the upper left corner of the edge detection result image 460. The first processing unit 113 may, for example, determine a region with width W11 and height H11 in the edge detection result image 460, and then determine the candidate image region 611 by aligning the upper left corner of this region with the initial position, but this is not limited to this. Specifically, the initial position is, for example, the position in the edge detection result image 460 with coordinates (x,y) = (0,0), and based on the preset width W11 and height H11, the coordinates A11(0,0), B11(W11,0), C11(0,H11), and D11(W11,H11) are determined as the four corner coordinates of the initial candidate image region 611, thereby defining the candidate image region 611.

[0146] In step S512, the first processing unit 113 calculates the grayscale parameters of all pixels in the candidate image region 611 corresponding to the corrected edge detection result image information, and determines whether the candidate image region 611 meets the preset conditions based on the grayscale parameters. If yes, the first processing unit 113 may continue to execute step S513; if no, the first processing unit 113 may continue to execute step S514.

[0147] The grayscale parameter is, for example, the average grayscale value or the sum of grayscale values ​​of all pixels in the candidate image region 611.

[0148] In embodiments where the considered grayscale parameter is the sum or average of grayscale values, the first processing unit 113 may, for example, first calculate the integral image information of the edge detection result image information, and then determine the grayscale parameter of the candidate image region 611 accordingly. The calculation of the integral image information can be performed after the corrected edge detection result image information is generated and before the region determination operation begins.

[0149] Based on the integral image information, the first processing unit 113 can calculate the sum of grayscale values ​​of the candidate image region 611 based on the aforementioned integral image information and the coordinates of the four corner points A11(0,0), B11(W11,0), C11(0,H11), and D11(W11,H11) of the candidate image region 611. Specifically, the integral image information includes the integral value of any coordinate in the edge detection result image information, and the sum of grayscale values ​​of the candidate image region 611 can be determined by the formula "integral value of coordinate D - integral value of coordinate B - integral value of coordinate C + integral value of coordinate A". The average grayscale value can be obtained by dividing the sum of grayscale values ​​by the total number of pixels in the candidate image region 611.

[0150] After determining the grayscale parameters corresponding to the candidate image region 611, the first processing unit 113 can determine whether the grayscale parameters are equal to the maximum possible value. If yes, the first processing unit 113 can determine that the candidate image region 611 meets the preset conditions; if no, the first processing unit 113 can determine that the candidate image region 611 does not meet the preset conditions.

[0151] The aforementioned maximum value is, for example, the grayscale parameter that is presented when the candidate image region under consideration is a full-color image region.

[0152] For example, assuming the background color under consideration is white (corresponding to a grayscale value of 255) and the grayscale parameter under consideration is the sum of grayscale values, then when the candidate image region under consideration is a full-background color image region, the corresponding maximum value is, for example, "255 * the total number of pixels in the candidate image region".

[0153] To give another example, assuming the background color under consideration is white and the grayscale parameter under consideration is the average grayscale value, then when the candidate image region under consideration is a full-color image region, the corresponding maximum value is 255.

[0154] Furthermore, when the first processing unit 113 determines that the grayscale parameter corresponding to a candidate image region is equal to the maximum possible value, this means that the candidate image region information (e.g., content information and / or geometric information) corresponding to this candidate image region does not include any obstacle edge 499a. In other words, if the projection device 120 uses the range of this candidate image region as the subsequent projection range, it can avoid this projection range from covering the obstacle 499.

[0155] On the other hand, such as Figure 6A The candidate image region 611 shown is such that when the first processing unit 113 determines that the grayscale parameter corresponding to a certain candidate image region is not equal to the maximum possible value, for example, less than the maximum possible value, this means that the candidate image region information corresponding to this candidate image region includes at least a part of the obstacle edge 499a. In other words, if the projection device 120 uses the range of this candidate image region 611 as the subsequent projection range, this projection range will still cover the obstacle 499.

[0156] In another embodiment, since there may be some imperfections on the projection surface (e.g., stains, dents, shadows, and / or it may not be completely white), even if the candidate projection area under consideration does not actually include the obstacle edge 499a, it may still be a non-full-color image area. In view of this case, the setting of the preset conditions can be included within a tolerance range.

[0157] For example, after determining the grayscale parameters corresponding to the candidate image region under consideration, the first processing unit 113 can determine whether the grayscale parameters are greater than a preset threshold. If yes, the first processing unit 113 can determine that the candidate image region under consideration meets the preset conditions; if no, the first processing unit 113 can determine that the candidate image region under consideration does not meet the preset conditions.

[0158] For example, assuming the background color under consideration is white and the grayscale parameter under consideration is the sum of grayscale values, the preset threshold can be set as "(255 - error value) * number of pixels in the candidate image area", where the error value can be set to a corresponding value (e.g., 2) according to the degree of defects / errors that the designer can tolerate.

[0159] To give another example, assuming the background color under consideration is white and the grayscale parameter under consideration is the average grayscale value, the preset threshold can be set to "(255 - error value)", but it is not limited to this.

[0160] exist Figure 6A In this scenario, since the candidate image region information (e.g., content information and / or geometric information) corresponding to the candidate image region 611 includes a part of the obstacle edge 499a, in step S512, it is determined that the candidate image region 611 does not meet the preset conditions, and then step S514 is executed to move the candidate image region along the first direction D1 by a first movement magnitude Xstep.

[0161] exist Figure 6A In this scenario, the first processing unit 113 can move the candidate image region 611 along the first direction D1 by a first movement magnitude Xstep. The first movement magnitude Xstep can be any value determined by the designer as needed, for example, the first movement magnitude can be a preset number of pixels (e.g., 20 pixels). The coordinates of the four corner points of the candidate image region 612 after the candidate image region 611 has been moved along the first direction D1 by the first movement magnitude Xstep are A12(Xstep,0), B12(Xstep+W11,0), C12(Xstep,H11), and D12(Xstep+W11,H11).

[0162] In step S515, the first processing unit 113 determines whether the moved candidate image region exceeds the edge detection result image 460 in the first direction D1. If yes, the first processing unit 113 continues to execute step S516; if no, the first processing unit 113 executes step S512.

[0163] exist Figure 6AIn this scenario, if the candidate image region 612, after being moved by the candidate image region 611 in the first direction D1, does not exceed the edge detection result image 460 in the first direction D1, then step S512 is executed accordingly. Specifically, whether the candidate image region 612 exceeds the edge detection result image 460 in the first direction D1 is determined by whether the X coordinate of the corner point B (Xstep+W11,0) of the candidate image region 612 is greater than the width of the edge detection result image 160.

[0164] In other words, the first processing unit 113 performs the same calculations and judgments on the candidate image region 612 as it does on the candidate image region 611, using the same method as calculating grayscale parameters and determining whether preset conditions are met.

[0165] Depend on Figure 6A As can be seen, since the candidate image region 612 still includes a part of the obstacle edge 499a, the first processing unit 113 may, for example, determine in step S512 that the candidate image region 612 does not meet the preset conditions, and then continue to execute step S514 to move the candidate image region along the first direction D1 by a first movement magnitude Xstep, so as to move to the next candidate image region 613 in the first direction D1.

[0166] In other words, in steps S512-S515, when a candidate image region is determined to not meet the preset conditions, it moves along the first direction D1 to the next candidate image region until the moved candidate image region exceeds the edge detection result image in the first direction D1, thereby sequentially determining whether the candidate image region at each position in the first direction D1 meets the preset conditions.

[0167] exist Figure 6A In the scenario where candidate image regions 611-613 still include the obstacle edge 499a, and candidate image region 614 extends beyond the edge detection result image in the first direction D1, step S516 is entered.

[0168] Please refer to Figure 6B It is a continuation Figure 6A A schematic diagram illustrating the region determination operation along the second direction D2.

[0169] In step S516, the first processing unit 113 changes to moving the candidate image region along the second direction D2 by a second movement magnitude Ystep based on the initial position in the first direction D1.

[0170] exist Figure 6BIn this scenario, when the first processing unit 113 executes step S516, it moves the candidate image region 611, which corresponds to the initial position in the first direction D1, along the second direction D2 by a second movement magnitude Ystep to form a candidate image region 621. In other words, the coordinates of the four corner points of the candidate image region 621 after the candidate image region 611 is moved along the second direction D2 by a second movement magnitude Ystep are A21(0,Ystep), B21(W11,Ystep), C21(0,H11+Ystep), and D21(W11,H11+Ystep).

[0171] The second movement amplitude Ystep can be set by the designer to any value as needed. The second movement amplitude can be different from or the same as the first movement amplitude. For example, the second movement amplitude is a preset number of pixels (e.g., 15 pixels).

[0172] Next, in step S517, the first processing unit 113 determines whether the moved candidate image region 611 exceeds the edge detection result image 460 in the second direction D2. If yes, the first processing unit 113 can continue to execute step S518; if no, the first processing unit 113 returns to executing step S512.

[0173] exist Figure 6B In this scenario, the candidate image region 611, after being moved in step S516, becomes candidate image region 621. The first processing unit 113 can proceed to step S512 after determining that candidate image region 621 does not exceed the edge detection result image 460 in the second direction D2. Specifically, this is determined by whether the Y-coordinate of the corner point C(0, H11+Ystep) of candidate image region 621 is greater than the height of edge detection result image 460.

[0174] In other words, when a candidate image region moves from its initial position in the first direction D1 along the second direction D2 without exceeding the edge detection result image 460, the process of steps S512-515 is entered again. The candidate image regions are moved sequentially along the first direction D1, and it is determined whether each candidate image region in the first direction D1 meets the preset conditions, until the candidate image region exceeds the edge detection result image 460 in the first direction D1. Then, steps S516-S517 are executed again.

[0175] Furthermore, in step S517, when the candidate image region after moving along the second direction D2 exceeds the edge detection result image 460, the first processing unit 113 proceeds to step S518.

[0176] exist Figure 6BIn the scenario where the process is executed to the point where the candidate image region 621, which is initially located in the first direction D1, moves along the second direction D2 by a second movement magnitude Ystep to form a candidate image region 631, and the candidate image region 631 extends beyond the edge detection result image 460 in the second direction D2, the process proceeds to step S518.

[0177] In step S518, the first processing unit 113 reduces the preset size. Then, in step S519, the first processing unit 113 determines whether the reduced preset size is smaller than the minimum preset size.

[0178] In one embodiment, the first processing unit 113 reduces the width W11 and height H11 by a specific ratio to determine the reduced preset size. For example, the first processing unit 113 multiplies the height H11 by a fixed reduction ratio to obtain a new height, and then multiplies the new height by a preset aspect ratio to obtain a new width. In this way, the reduced specified size can still have a preset aspect ratio.

[0179] The minimum specified size corresponds to the minimum allowable projection range. If the reduced preset size is smaller than the minimum preset size, it means that the projection device 120 cannot avoid the obstacle 499 while providing a sufficiently large projection range. Therefore, the first processing unit 113 proceeds to step S520 and determines that the corrected edge detection result image 460 does not contain the maximum unobstructed area.

[0180] If the corrected edge detection result image 460 is determined to not contain the maximum obstacle-free area, the first processing unit 113 terminates the projection obstacle avoidance function. In addition, the first processing unit 113 may also control the display unit 115 to display an obstacle avoidance failure notification screen, or transmit obstacle avoidance failure notification image information to the projection device 120 for projection by the projection device 120, thereby notifying the user that the projection obstacle avoidance function has failed.

[0181] On the other hand, if the reduced preset size is not smaller than the minimum preset size, the first processing unit 113 returns to steps S511-S517 to try again to find a projection range that can avoid the obstacle 499 based on the reduced preset size. In other words, the projection device 120 still has the opportunity to provide a sufficiently large projection range while avoiding the obstacle 499. The following will supplement... Figure 7A to Figure 7B Further explanation is needed.

[0182] Please refer to Figure 7A and Figure 7B This is a schematic diagram illustrating the region determination operation based on a reduced preset size. The reduced preset size is a preset size with a width W12 and a height H12.

[0183] For example, in Figure 7A to Figure 7BIn the scenario, the first processing unit 113 sequentially obtains candidate image regions 711-714 at a first movement amplitude Xstep according to steps S511-515, and sequentially calculates the grayscale parameters of candidate image regions 711-713 and determines whether the grayscale parameters meet the preset conditions; when the moved candidate image region 714 exceeds the corrected edge detection result image 460 in the first direction D1, it enters steps S516-S517, and instead moves the candidate image region 711 based on the initial position in the first direction D1 along the second direction D2 by a second movement amplitude Ystep to obtain candidate image region 721, and executes steps S511-515; when the candidate image region 731 after moving by a second movement amplitude Ystep along the second direction D2 exceeds the corrected edge detection result image 460 in the second direction D2, it enters step S518 again to reduce the preset size.

[0184] In an embodiment of the present invention, Figure 5A , Figure 5B The process will be executed recursively according to the above steps S511-520 until the first processing unit 113 determines in step S512 that the candidate image region currently being considered meets the preset conditions, or determines in step S521 that the reduced preset size is smaller than the preset size, but it is not limited to these.

[0185] Please refer to Figure 8 This is a schematic diagram illustrating the determination of the maximum barrier-free area according to one embodiment of the present invention.

[0186] exist Figure 8 In this context, it is assumed that the preset size under consideration has a width W18 and a height H18, and the first processing unit 113 determines the candidate image region 811 accordingly.

[0187] Depend on Figure 8 It can be seen that the candidate image region (e.g., content information and / or geometric information) corresponding to the candidate image region 811 does not include any obstacle edge 499a. In this case, the first processing unit 113 will determine that the candidate image region 811 meets the preset conditions based on the grayscale parameters corresponding to the candidate image region 811, and then continue to execute step S513.

[0188] Accordingly, in step S513, the first processing unit 113 can set the candidate image region 811 that meets the preset conditions as the maximum unobstructed area. In other words, if the projection device 120 uses the projection surface range corresponding to the candidate image region 811 as the subsequent projection range, it can avoid the projected image covering the obstacle 499.

[0189] Please refer to this again. Figure 2After setting the maximum unobstructed area according to step S260, in step S270, the first processing unit 113 generates multiple projection range coordinates based on the maximum unobstructed area (e.g., candidate image area 811) and sends the multiple projection range coordinates to the projection device 120.

[0190] The maximum unobstructed area is the region defined by the coordinates of multiple corner points in the edge detection result image 460. Specifically, for example, the coordinates of the four corner points of the candidate image region 811 are An(0,0), Bn(W18,0), Cn(0,H18), and Dn(W18,H18).

[0191] In one embodiment, the first processing unit 113 may obtain multiple corrected projection corner coordinates used by the projection device 120 when projecting the first corrected image 310 (e.g., projection corner coordinates obtained after trapezoidal correction of the projection device 120). Then, the first processing unit 113 may perform a mapping transformation based on the multiple corner coordinates and the multiple corrected projection corner coordinates to generate the multiple projection range coordinates.

[0192] Accordingly, after the projection device 120 receives the multiple projection range coordinates from the mobile device 110, the projection device 120 can adjust the projection range so that the adjusted projection range can correspond to the maximum unobstructed area (e.g., candidate image area 811).

[0193] In one embodiment, after the first processing unit 113 generates the plurality of projection range coordinates in step S270, the first processing unit 113 may first control the display unit 115 to display the first reference image 412, and then mark the image area corresponding to the largest unobstructed area (e.g., candidate image area 811) in the first reference image 412 according to the plurality of projection range coordinates. Afterwards, the first processing unit 113 may further control the display unit 115 to display a confirmation correction button for user confirmation.

[0194] After the user agrees to the maximum accessibility area by, for example, triggering the confirmation correction button, the first processing unit 113 can then send the coordinates of the plurality of projection ranges to the projection device 120.

[0195] In another embodiment, after the projection device 120 receives the plurality of projection range coordinates, it can also project an adjustment preview projection image based on them, and present the expected projection range in the adjustment preview projection image according to the plurality of projection range coordinates (for example, marking the expected projection range in the projection image with corresponding outer frames). Furthermore, the first processing unit 113 can then control the display unit 115 to display a confirmation correction button for user confirmation.

[0196] After the user agrees to the maximum unobstructed area by, for example, triggering the confirmation correction button, the projection device 120 can then substantially adjust the projection range to the expected projection range.

[0197] In some embodiments, some operations performed by the mobile device 110 (e.g., steps S220 to S270) may be performed by a remote server connected to the mobile device 110. In one embodiment, when performing step S270, the remote server may send the multiple projection range coordinates to the projection device via the mobile device 110 after determining the multiple projection range coordinates, but this is not limited to this.

[0198] Please refer to Figure 9 This is a flowchart illustrating a projection obstacle avoidance method according to a second embodiment of the present invention. The projection obstacle avoidance method of the second embodiment includes steps S910-S970, and can be achieved by means of... Figure 1 The projection system 100 of the first embodiment shown is implemented. Referring to the following... Figure 1 The projection system 100 shown illustrates the steps of the second embodiment.

[0199] In step S910, the camera unit 111 captures a first reference image, wherein the first reference image includes a first correction image projected onto the projection surface by the projection device 120 according to the first correction image information, and the first correction image includes a correction pattern.

[0200] In this embodiment, details of step S910 can be found in [reference needed]. Figure 2 The description of step S210 in the first embodiment shown will not be repeated here.

[0201] In step S920, camera unit 111 captures a second reference image, wherein the second reference image includes a second corrected image 350 projected onto a projection surface by projection device 120, and the second corrected image 350 is, for example, a background color image. Specifically, the background color image is a monochrome image, for example, a completely white image.

[0202] The following will be further supplemented Figure 10A to Figure 11B The experimental images based on the second embodiment of the present invention will be used for illustration. Figure 10A It is the original first reference image captured by the camera unit of the mobile device; Figure 10B It is the first reference image after preprocessing; Figure 11A It is the original second reference image captured by the camera unit of the mobile device; Figure 11B It is the second reference image after preprocessing.

[0203] refer to Figure 10AThe original first reference image 411 is, for example, the original image obtained by the camera unit 111 taking a picture of the first corrected image 310 projected onto the projection surface in response to the user's trigger.

[0204] Additionally, refer to Figure 11A The original second reference image 1011 is, for example, the original image obtained by the camera unit 111 capturing the second corrected image 350 projected onto the projection surface in response to a user's trigger. Preferably, the user should operate the camera unit 111 to capture the second corrected image 350 projected onto the projection surface using the same settings / position as when capturing the first corrected image 310, thereby capturing the second reference image 1011 and generating second reference image information.

[0205] In step S920, the first processing unit 113 receives first reference image information corresponding to the first reference image 412 and second reference image information corresponding to the second reference image 1012 from the camera unit 111, and obtains first correction image information corresponding to the first correction image.

[0206] Please refer to Figure 10B In some embodiments, the first processing unit 113 preprocesses the original first reference image information to generate first reference image information corresponding to the preprocessed first reference image 412. Furthermore, the reference... Figure 11B The first processing unit 113 may also perform the same preprocessing on the second reference image information as on the first reference image information to generate second reference image information corresponding to the preprocessed second reference image 1012.

[0207] For details regarding the first corrected image 310 and related first corrected image information of this embodiment, as well as the method of obtaining them, please refer to the description of the first embodiment above, which will not be repeated here.

[0208] In step S930, the first processing unit 113 calculates multiple matching image feature point pairs based on the first reference image information and the first corrected image information. Detailed methods for step S930 can be found in all relevant descriptions of step S230 of the aforementioned first embodiment, and will not be repeated here.

[0209] In step S940, the first processing unit 113 performs mapping and transformation on the region information corresponding to the second corrected image 350 in the second reference image information based on the plurality of matching image feature point pairs to generate obstacle avoidance image information.

[0210] Specifically, in step S940, the first processing unit 113 first generates a first transformation matrix based on the plurality of matching image feature point pairs, mapping the coordinate system of the first corrected image to the coordinate system of the first reference image, and then performs an inverse matrix operation on the first transformation matrix to generate a second transformation matrix. In this embodiment, the detailed means and principles for generating the first and second transformation matrices in step S940 are the same as those for generating the first and second transformation matrices in step S240 of the first embodiment, and will not be repeated here.

[0211] Next, the first processing unit 113 uses the first transformation matrix to map the first corrected image information to the second reference image information, so as to determine the region information in the second reference image information corresponding to the second corrected image 350.

[0212] The following will be further supplemented Figure 11C to Figure 11D The experimental images based on the second embodiment of the present invention will be used for illustration. Figure 11C It is the image region in the second reference image after mapping and transformation that corresponds to the first corrected image in the second embodiment of the present invention; Figure 11D It is Figure 11C The obstacle avoidance image is generated after the image area is mapped and transformed by another method.

[0213] Please refer to Figure 11B and Figure 11C The region information in the second reference image information corresponding to the second corrected image 350 may, for example, correspond to the image region 1110 contained in the second reference image 1012. That is, the region information in the second reference image 1012 corresponding to the second corrected image 350 may include, for example, geometric information and content information related to the image region 1110.

[0214] Next, the first processing unit 113 uses the second transformation matrix to map the area information into obstacle avoidance image information.

[0215] In this embodiment, the first reference image 412 and the second reference image 1012 are captured by the mobile device 110 at the same setting / position. Therefore, the first transformation matrix and the second transformation matrix generated based on the matching image features between the first reference image 412 and the first corrected image 310 can produce the same perspective transformation effect between the second reference image 412 and the second corrected image 350, thereby determining the image region 1110 corresponding to the second corrected image 350 in the second reference image 412.

[0216] Please refer to Figure 11D The obstacle avoidance image information may correspond to obstacle avoidance image 1120, for example.

[0217] In step S950, the first processing unit 113 performs edge detection calculations on the obstacle avoidance image information to generate edge detection result image information corresponding to the edge detection result image.

[0218] Depend on Figure 11B to Figure 11D As can be seen, the difference between this embodiment and the first embodiment lies in that, since the obstacle avoidance image 1120 in this embodiment is generated by mapping and transforming the second reference image 1012, and the second reference image 1012 is generated by capturing the second reference image 350, and the second reference image 350 itself does not include such... Figure 3A The correction pattern 311 shown will not contain information corresponding to the correction pattern 311 in the edge detection result image generated from the obstacle avoidance image 1120. Therefore, after the first processing unit 113 performs edge detection calculations on the obstacle avoidance image information to generate edge detection result image information, there is no need to perform region masking to exclude the pattern edges corresponding to the correction pattern. In other words, after executing step S950, the edge detection result image information generated by the first processing unit 113 is as follows: Figure 4G The edge detection result image 460 shown does not include the pattern edge of the correction pattern, and can be directly used in subsequent steps S960-S970 (corresponding to...). Figure 2 The maximum unobstructed area determination in steps S260-S270 of the first embodiment.

[0219] In step S960, the first processing unit 113 performs region determination calculations on the edge detection result image information to set the maximum unobstructed area in the edge detection result image 460. Specifically, in this embodiment, the detailed means and principles of step S960 are the same as those of step S260 in the first embodiment, and therefore can be referred to the aforementioned detailed means and principles. Figure 5A to Figure 8 The explanation will not be repeated here.

[0220] In step S970, the first processing unit 113 generates multiple projection range coordinates based on the maximum unobstructed area and sends the multiple projection range coordinates to the projection device 120.

[0221] In this embodiment, the details of step S970 can be referred to the relevant description of step S270 in the first embodiment, and will not be repeated here.

[0222] In summary, in this invention, the first corrected image 310 containing the correction pattern 311 mainly enables the mobile device 110 to obtain matching image feature point pairs between the first reference image 410 and the first corrected image 310, thereby calculating the transformation matrix used for mapping transformation. Furthermore, the main difference between the second embodiment and the first embodiment is that the second embodiment additionally projects a second corrected image 350 with a full background color using the projection device 120, allowing the mobile device 110 to directly obtain the second reference images 1011 and 1012 that do not contain information related to the correction pattern 31, thus omitting region masking calculations and directly using them for subsequent maximum accessibility area determination calculations.

[0223] In summary, the projection obstacle avoidance method of the present invention has at least one of the following advantages: (1) Automatic obstacle recognition: By capturing images through the camera unit of the mobile device and performing algorithm processing, the optimal projection range that can avoid obstacles can be automatically found, so as to facilitate the projection device to perform the correction setting of the projection area; (2) Convenient operation interface provided through mobile device application: There is no need to search for the obstacle avoidance function setting in the projection device through the remote control. The user only needs to install the application on the mobile device with the photography function and communicate with the projection device through the application to take pictures of the projected image for setting; (3) Automated correction and projection area adjustment: The user does not need to manually set the four corner coordinates of the image one by one to avoid obstacles. The system can automatically obtain the coordinates of the four corner points of the projection area after obstacle avoidance through the algorithm of the mobile device application and provide such information to the projection device to complete the correction setting, thereby effectively reducing the manual operation time; (4) Improved projection setting efficiency and accuracy: Compared with the traditional method of manually adjusting the four corner coordinates, the automatic obstacle avoidance mechanism described in the present invention can quickly complete the setting of the maximum usable projection range, greatly simplifying the setting process and improving the overall accuracy.

[0224] The above description is merely a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. Any simple equivalent changes and modifications made in accordance with the claims and description of the invention are still within the scope of this patent. Furthermore, no embodiment or claim of the present invention needs to achieve all the objectives, advantages, or features disclosed in the invention. In addition, the abstract and title are only used to assist in patent document retrieval and are not intended to limit the scope of the invention. Moreover, the terms "first," "second," etc., mentioned in this specification or claims are only used to name elements or distinguish different embodiments or scopes, and are not used to limit the upper or lower limit of the number of elements.

Claims

1. A projection obstacle avoidance method, characterized in that, The projection obstacle avoidance method is performed by a mobile device, which includes a camera unit and a processing unit coupled to the camera unit. The mobile device is communicatively connected to a projection device. The projection obstacle avoidance method includes: The camera unit captures a first reference image, wherein the first reference image includes a first correction image projected onto a projection surface by the projection device based on first correction image information, and the first correction image includes a correction pattern; and The processing unit performs the following steps: Receive first reference image information corresponding to the first reference image from the camera unit, and obtain first correction image information corresponding to the first correction image; Multiple matching image feature point pairs are calculated based on the first reference image information and the first corrected image information; Based on the multiple matching image feature point pairs, the region information in the first reference image information corresponding to the first corrected image is mapped and transformed to generate obstacle avoidance image information. The obstacle avoidance image information is subjected to edge detection operation to generate edge detection result image information corresponding to the edge detection result image, and the part of the edge detection result image information corresponding to the correction pattern is corrected; Perform region determination calculations on the corrected edge detection result image information to set the maximum unobstructed area in the edge detection result image, and The multiple projection range coordinates are generated based on the maximum unobstructed area, and the multiple projection range coordinates are sent to the projection device.

2. The projection obstacle avoidance method according to claim 1, characterized in that, The step of performing the mapping transformation on the region information corresponding to the first corrected image in the first reference image information based on the multiple matching image feature point pairs to generate the obstacle avoidance image information further includes the following steps: Based on the first reference image information and the first corrected image information, feature point detection and matching calculation are performed to generate the plurality of matching image feature point pairs between the first reference image and the first corrected image. A first transformation matrix is ​​generated based on the multiple matching image feature point pairs, and an inverse matrix operation is performed on the first transformation matrix to generate a second transformation matrix; The first correction image information is mapped to the first reference image information using the first transformation matrix to determine the region information in the first reference image information corresponding to the first correction image; and The second transformation matrix is ​​used to map the region information into the obstacle avoidance image information.

3. The projection obstacle avoidance method according to claim 1, characterized in that, The step of correcting the portion of information corresponding to the corrected pattern in the edge detection result image information further includes the following steps: Obtain first image region information of the first image region occupied by the correction pattern in the obstacle avoidance image information; Determine the second image region information corresponding to the first image region information from the edge detection result image information; The edge detection result image information is masked according to the second image region information to exclude the pattern edges in the edge detection result image that correspond to the correction pattern.

4. The projection obstacle avoidance method according to claim 1, characterized in that, The step of performing the region determination operation on the corrected edge detection result image information to set the maximum unobstructed region in the edge detection result image further includes the following steps: (a) Determine a candidate image region in the edge detection result image according to a preset size, wherein the preset size has a preset aspect ratio and is smaller than the corrected edge detection result image; (b) Calculate the grayscale parameters of all pixels in the candidate image region corresponding to the corrected edge detection result image information, and determine whether the candidate image region meets the preset conditions based on the grayscale parameters; (c) In response to determining that the candidate image region meets the preset condition, the candidate image region that meets the preset condition is set as the maximum unobstructed area; (d) In response to the determination that the candidate image region does not meet the preset condition, the candidate image region is moved and the process returns to step (b).

5. The projection obstacle avoidance method according to claim 4, characterized in that, Step (a) of determining the candidate image region in the corrected edge detection result image based on the preset size further includes the following steps: The initial position in the corrected edge detection result image determines the candidate image region corresponding to the specified size; Step (d) involves determining that the candidate image region does not meet the preset condition, and moving the candidate image region includes the following steps: The candidate image region is moved along a first direction by a first movement amount; and If the moved candidate image region extends beyond the edge detection result image in the first direction, the candidate image region is instead positioned based on its initial position in the first direction. Move by a second movement amount along the second direction.

6. The projection obstacle avoidance method according to claim 4, characterized in that, Step (b) of calculating the grayscale parameters of all pixels in the candidate image region and determining whether the candidate image region meets the preset conditions based on the grayscale parameters further includes: Determine whether the grayscale parameter is equal to the possible maximum value; If so, determine that the candidate image region meets the preset conditions.

7. The projection obstacle avoidance method according to claim 4, characterized in that, Step (b) of calculating the grayscale parameters of all pixels in the candidate image region corresponding to the edge detection result image information, and determining whether the candidate image region meets the preset conditions based on the grayscale parameters, further includes the following steps: Determine whether the grayscale parameter is greater than a preset threshold; If so, determine that the candidate image region meets the preset conditions.

8. The projection obstacle avoidance method according to claim 4, characterized in that, The projection obstacle avoidance method includes: Calculate the integral image information of the corrected edge detection result image information; Step (b) of calculating the grayscale parameters of all pixels in the candidate image region and determining whether the candidate image region meets the preset conditions based on the grayscale parameters further includes the following steps: The sum or average gray level of all pixels in the candidate image region is calculated based on the integral image information, wherein the gray level parameter is the sum or average gray level of the gray level.

9. The projection obstacle avoidance method according to claim 4, characterized in that, The projection obstacle avoidance method also includes the following steps: (e) In response to the moved candidate image region extending beyond the edge detection result image in the second direction, the preset size is reduced; (f) In response to the determination that the reduced preset size is not less than the minimum preset size, return to step (a); and (g) In response to the determination that the reduced preset size is smaller than the minimum preset size, it is determined that the edge detection result image does not contain the maximum barrier-free area.

10. The projection obstacle avoidance method according to claim 1, characterized in that, The maximum unobstructed area is the region defined by the coordinates of multiple corner points in the edge detection result image, and the step of generating the multiple projection range coordinates based on the maximum unobstructed area further includes: Obtain the coordinates of multiple corrected projection corner points used by the projection device when projecting the first corrected image; A mapping transformation is performed based on the multiple corner point coordinates and the multiple corrected projected corner point coordinates to generate the multiple projection range coordinates.

11. A projection obstacle avoidance method, characterized in that, The projection obstacle avoidance method is performed by a mobile device, which includes a camera unit and a processing unit coupled to the camera unit. The mobile device is communicatively connected to a projection device. The projection obstacle avoidance method includes: The camera unit captures a first reference image, wherein the first reference image includes a first correction image projected onto a projection surface by the projection device, and the first correction image includes a correction pattern. The camera unit captures a second reference image, wherein the second reference image includes a second corrected image projected onto the projection surface by the projection device, and the second corrected image is a background color image; and The processing unit performs the following steps: Receive first reference image information corresponding to the first reference image and second reference image information corresponding to the second reference image from the camera unit, and obtain first correction image information corresponding to the first correction image; Multiple matching image feature point pairs are calculated based on the first reference image information and the first corrected image information; Based on the multiple matching image feature point pairs, the region information in the second reference image information corresponding to the first corrected image is mapped and transformed to generate obstacle avoidance image information. Edge detection operations are performed on the obstacle avoidance image information to generate edge detection result image information corresponding to the edge detection result image; Perform region determination calculations on the edge detection result image information to set the maximum unobstructed area in the edge detection result image; and Multiple projection range coordinates are generated based on the maximum unobstructed area, and the multiple projection range coordinates are sent to the projection device.

12. The projection obstacle avoidance method according to claim 11, characterized in that, The step of mapping and transforming the region information corresponding to the first corrected image in the second reference image information based on the multiple matching image feature point pairs to generate the obstacle avoidance image information includes the following steps: Based on the first reference image information and the first corrected image information, feature point detection and matching calculation are performed to generate the plurality of matching image feature point pairs between the first reference image and the first corrected image. A first transformation matrix is ​​generated based on the multiple matching image feature point pairs, and an inverse matrix operation is performed on the first transformation matrix to generate a second transformation matrix; The first transformation matrix is ​​used to map the first corrected image information to the second reference image information to determine the region information in the second reference image information corresponding to the second corrected image; and The second transformation matrix is ​​used to map the region information into the obstacle avoidance image information.

13. The projection obstacle avoidance method according to claim 11, characterized in that, The step of performing the region determination operation on the edge detection result image information to determine the optimal barrier-free region in the edge detection result image includes the following steps: (a) Determine candidate image regions in the edge detection result image according to a preset size, wherein the preset size has a preset aspect ratio; (b) Calculate the grayscale parameters of all pixels in the candidate image region corresponding to the edge detection result image information, and determine whether the candidate image region meets the preset conditions based on the grayscale parameters; (c) In response to determining that the candidate image region meets the preset condition, the candidate image region that meets the preset condition is set as the maximum unobstructed area; (d) In response to the determination that the candidate image region does not meet the preset condition, the candidate image region is moved and the process returns to step (b).

14. The projection obstacle avoidance method according to claim 13, characterized in that, Step (a) of determining the candidate image region in the edge detection result image according to the preset size further includes the following steps: The initial position in the edge detection result image is determined to correspond to the candidate image region of the preset size; Step (d) involves determining that the candidate image region does not meet the preset condition, and moving the candidate image region further includes the following steps: The candidate image region is moved along a first direction by a first movement amount; and In response to the candidate image region moving beyond the edge detection result image in the first direction, the candidate image region is instead moved by a second movement amount in the second direction based on its initial position in the first direction.

15. The projection obstacle avoidance method according to claim 13, characterized in that, Step (b) further includes calculating the grayscale parameters of all pixels in the candidate image region corresponding to the edge detection result image information, and determining whether the candidate image region meets the preset conditions based on the grayscale parameters: Determine whether the grayscale parameter is equal to the possible maximum value; If so, determine that the candidate image region meets the preset conditions.

16. The projection obstacle avoidance method according to claim 13, characterized in that, Step (b) further includes calculating the grayscale parameters of all pixels in the candidate image region corresponding to the edge detection result image information, and determining whether the candidate image region meets the preset conditions based on the grayscale parameters: Determine whether the grayscale parameter is greater than a preset threshold; If so, determine that the candidate image region meets the preset conditions.

17. The projection obstacle avoidance method according to claim 13, characterized in that, The projection obstacle avoidance method also includes: Calculate the integral image information of the edge detection result image information; Step (b) of calculating the grayscale parameters of all pixels in the candidate image region and determining whether the candidate image region meets the preset conditions based on the grayscale parameters further includes the following steps: The sum or average gray level of all pixels in the candidate image region is calculated based on the integral image information, wherein the gray level parameter is the sum or average gray level of the gray level.

18. The projection obstacle avoidance method according to claim 13, characterized in that, The projection obstacle avoidance method also includes the following steps: (e) In response to the moved candidate image region extending beyond the edge detection result image in the second direction, the finger preset size is reduced; (f) In response to the determination that the reduced preset size is not less than the minimum preset size, return to step (a); and (g) In response to the determination that the reduced preset size is smaller than the minimum preset size, it is determined that the edge detection result image does not contain the maximum barrier-free area.

19. The projection obstacle avoidance method according to claim 11, characterized in that, The maximum unobstructed area is the region defined by the coordinates of multiple corner points in the edge detection result image, and the step of generating the multiple projection range coordinates based on the optimal unobstructed area further includes the following steps: Obtain the coordinates of multiple corrected projection corner points used by the projection device when projecting the first corrected image; A mapping transformation is performed based on the multiple corner point coordinates and the multiple corrected projected corner point coordinates to generate the multiple projection range coordinates.

20. A projection system, characterized in that, The projection system includes a projection device and a moving device, wherein: The projection device is used to project a first correction image onto a projection surface based on first correction image information, the first correction image including a correction pattern; and The mobile device is communicatively connected to the projection device and configured to perform the projection obstacle avoidance method according to claim 1; The projection device sets the projection range according to the multiple projection range coordinates.

21. The projection system according to claim 20, characterized in that, The mobile device includes: A camera unit is used to capture the first reference image; The first storage unit is used to store the first application and the first corrected image information of the first corrected image; A first processing unit, coupled to the camera unit and the first storage unit, is used to execute the first application to execute the projection obstacle avoidance method; A first communication unit, coupled to the first processing unit, is used to send the plurality of projection range coordinates to the projection device; and The display unit, coupled to the first processing unit, is used to display the captured first reference image or the operation interface of the first application.

22. The projection system according to claim 21, characterized in that, The user interface of the first application includes the identity information of the projection device, and the first processing unit is configured to: In response to the determination that the identity information of the projection device has been selected, the first communication unit is controlled to establish a connection with the projection device. as well as In response to the determination that the obstacle avoidance function in the operation interface of the first application is triggered, the first communication unit is controlled to send an obstacle avoidance function activation command to the projection device through the connection.

23. The projection system according to claim 20, characterized in that, The projection device includes: The second communication unit is used to receive the obstacle avoidance function activation command; The second storage unit stores the second application and the first corrected image information of the first corrected image; The second processing unit, coupled to the second communication unit and the second storage unit, is used to execute the second application in response to the obstacle avoidance function activation command, so as to read the first corrected image information from the second storage unit; An image processing unit, coupled to the second processing unit, is used to receive the first corrected image information from the second processing unit; A lighting system used to generate a beam of light; A light modulation module is coupled to the image processing unit and the illumination system, and is controlled by the image processing unit to convert the illumination beam into an image beam corresponding to the first corrected image based on the first corrected image information; A projection lens, coupled to the light modulation module, is used to project the image beam corresponding to the first corrected image.

24. The projection system according to claim 23, characterized in that, The second processing unit also performs: Based on the device posture information of the projection device, image trapezoidal correction is performed to generate multiple corrected projection corner point coordinates; The second communication unit is controlled to send the coordinates of the plurality of corrected projected corner points to the mobile device; and Based on the coordinates of the plurality of corrected projection corner points, the adjusted first corrected image information is generated and sent to the image processing unit; The image processing unit also performs the following: The light modulation module is controlled to convert the illumination beam into an image beam corresponding to the adjusted first corrected image based on the adjusted first corrected image information; The projection lens also performs the following: The image beam is projected corresponding to the adjusted first corrected image.

25. A projection system, characterized in that, The projection system includes a projection device and a moving device, wherein: The projection device is used to project a first corrected image onto a projection surface based on first corrected image information, and to project a second corrected image onto the projection surface based on second corrected image information, wherein the first corrected image includes a corrected pattern, and the second corrected image is a background color image; and The mobile device is communicatively connected to the projection device and configured to perform the projection obstacle avoidance method according to claim 11; The projection device sets the projection range according to the multiple projection range coordinates.

26. The projection system according to claim 25, characterized in that, The mobile device includes: A camera unit is used to capture the first reference image, wherein the first reference image includes a first correction image projected onto a projection surface by the projection device according to the first correction image information, and the first correction image includes a correction pattern. The first storage unit is used to store the application and the first corrected image information of the first corrected image; A first processing unit, coupled to the camera unit and the first storage unit, is used to execute the application program to execute the projection obstacle avoidance method; A first communication unit, coupled to the first processing unit, is used to send the plurality of projection range coordinates to the projection device; and The display unit, coupled to the first processing unit, is used to display the captured first reference image or the operation interface of the application.

27. The projection system according to claim 26, characterized in that, The user interface of the application includes the identity information of the projection device, and the first processing unit is configured to: In response to the determination that the identity information of the projection device has been selected, the first communication unit is controlled to establish a connection with the projection device. as well as In response to the determination that the obstacle avoidance function in the operation interface of the application is triggered, the first communication unit is controlled to send an obstacle avoidance function activation command to the projection device through the connection.

28. The projection system according to claim 25, characterized in that, The projection device includes: The second communication unit is used to receive the obstacle avoidance function activation command; The second storage unit stores the application and the first corrected image information of the first corrected image; The second processing unit, coupled to the second communication unit and the second storage unit, is used to execute the application in response to the obstacle avoidance function activation command, so as to read the first corrected image information from the second storage unit; An image processing unit, coupled to the second processing unit, is used to receive the first corrected image information from the second processing unit; A lighting system used to generate a beam of light; A light modulation module, coupled to the image processing unit and the illumination system, and controlled by the image processing unit to convert the illumination beam into an image beam corresponding to the first corrected image based on the first corrected image information; and A projection lens, coupled to the light modulation module, is used to project the image beam corresponding to the first corrected image.

29. The projection system according to claim 28, characterized in that, The second processing unit also performs: Based on the device posture of the projection device, image trapezoidal correction is performed to generate multiple corrected projection corner point coordinates; The second communication unit is controlled to send the coordinates of the plurality of corrected projected corner points to the mobile device; Based on the coordinates of the plurality of corrected projection corner points, the adjusted first corrected image information is generated and sent to the image processing unit; The image processing unit also performs the following: The light modulation module is controlled to convert the illumination beam into an image beam corresponding to the adjusted first corrected image based on the adjusted first corrected image information; The projection lens also performs the following: The image beam is projected corresponding to the adjusted first corrected image.

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