Sensor and system for biometric sensing having multi-segment architecture, and methods of using the same

Abstract

This invention provides a multi-segment pixel matrix, sensor or device, system, and method for biometric sensing. The device or system includes a sensor having a pixel matrix comprising two or more pixel arrays, the pixel arrays being logically divided segments within the pixel matrix. The pixel matrix may include both thermally sensing pixels and capacitively sensing nodes. The device or system may include a plurality of application-specific integrated circuits (ASICs) coupled to the sensor. Each ASIC is configured to capture image data of a biometric pattern measured by at least one pixel array. Each pixel array is independently driven and scanned by one or more of the plurality of ASICs. The device or system further includes a microcontroller unit coupled to the plurality of ASICs for processing the image data and / or controlling the operation of the system. The sensor may be a fingerprint sensor.

Description

Technical Field

[0001] The present invention generally relates to a device or apparatus and method for measuring a pattern in a portion of a thermally conductive surface. More specifically, the disclosed object relates to a device or apparatus for biosensing (such as a fingerprint sensor), a system, and a method for measuring or capturing an image of a biometric (e.g., fingerprint) pattern. Prior Technology

[0002] Fingerprint sensors are a form of technology used to provide biometric security. The intricate pattern formed by the bumps and depressions on the skin of the finger can be mapped by a sensor array, and their basic operating principles vary. Some sensors utilize thermal signals, while others use electrical, pressure, or light signals. Active sensors respond to a given stimulus and quantify a specific physical parameter. The level of accuracy is limited by the physical principles used to read the fingerprint pattern. Furthermore, immunity to environmental variables such as dust or humidity is also important when performing a fingerprint scan.

[0003] Fingerprint sensors are typically used in electronic devices to verify user identity and restrict access unless the sensor verifies that an authorized user is attempting to use the device. For example, some smart credit cards require user verification via a fingerprint sensor before use. Fingerprint sensors are also included in computing devices—such as smartphones, tablets, laptops, and point-of-sale devices—to ensure that only authorized users can unlock and use these devices. Summary of the Invention

[0004] The present invention provides a multi-segment pixel matrix, sensor or device, system and method for biosensing.

[0005] According to some embodiments, a system for biosensing includes a sensor comprising a pixel matrix having two or more pixel arrays as independent segments logically divided within the pixel matrix. The system further includes a plurality of application-specific integrated circuits (ASICs) coupled to the sensor. Each ASIC is configured to capture image data of a biometric pattern of an object measured by at least one pixel array. Each pixel array is configured to be independently driven and scanned by one or more of the plurality of ASICs. The system may further include a microcontroller unit (MCU) coupled to one of the plurality of ASICs. The MCU includes one or more processors and at least one tangible, non-transitory machine-readable medium using one or more program codes configured to process the image data and / or control the operation of the system. In some embodiments, the plurality of ASICs and the sensor are housed together within a biosensing device.

[0006] In some embodiments, the pixel matrix comprises any suitable number of pixel arrays, for example, from 2 to about 12 pixel arrays. The number of such pixel arrays (or segments) may be any integer in the range of 2 to 12.

[0007] The sensor may further include a plurality of support circuits. Each pixel array is connected to at least one support circuit. In some embodiments, the sensor in the system may further include a plurality of switches. Each switch is connected to one or more support circuits and one or more ASICs. Each pixel array is configured to be independently driven and scanned by one or more of the plurality of ASICs through one or more switches.

[0008] In some embodiments, each pixel array includes a plurality of pixels disposed in a plurality of columns and a plurality of rows. Each pixel array includes a thermally sensing pixel configured to operate based on an active thermal sensing principle, wherein a power thermal pulse is applied to each pixel array and the measurement corresponds to a response of a biometric pattern. For thermal sensing, one pixel in each pixel array may include one or more diodes connected in series between a pixel column line and a pixel row line.

[0009] According to some embodiments, each pixel array further includes a capacitive sensing grid having capacitive sensing nodes distributed throughout the pixel array. The system or device may further include auxiliary circuitry as a separate integrated circuit for the capacitive sensing grid, either within a respective ASIC, an MCU, or external to the respective ASIC or MCU. The capacitive sensing grid is connected to the auxiliary circuitry.

[0010] Through this MCU, the system is configured to perform the functions and steps described herein. For example, these steps include: detecting the presence of an object with a biometric pattern on the sensor; performing a coarse scan by scanning a portion of pixels in a pixel array to determine a contact boundary between the object and the sensor; and selectively performing a detailed scan within the contact boundary to provide image data of the biometric pattern. These steps may also include steps for detecting rolling motion and position, combining images, and processing and comparing image data, as described in this invention.

[0011] In another embodiment, the present invention provides a sensor or device for biometric sensing. This device includes: a sensor comprising a pixel matrix having two or more pixel arrays, the pixel arrays being logically divided into separate segments within the pixel matrix; and a plurality of application-specific integrated circuits (ASICs) coupled to the sensor. Each ASIC is configured to capture image data of a biometric pattern of an object measured by at least one pixel array. Each pixel array is configured to be independently driven and scanned by one or more of the plurality of ASICs. In some embodiments, the sensor is a fingerprint sensor, the object is a finger, and the biometric pattern is a fingerprint.

[0012] In some embodiments, each pixel array includes a plurality of pixels disposed in a plurality of columns and a plurality of rows, and the plurality of pixels includes thermal sensing pixels. Each pixel array may further include a capacitive sensing grid having capacitive sensing nodes distributed in each pixel array. The capacitive sensing grid is configured to detect the presence of an object and / or the rolling motion and position of the object. The capacitive sensing nodes may be mutual capacitance sensing nodes or self-capacitance sensing nodes. The self-capacitance sensing nodes are configured to be passively matrix-addressed or actively matrix-addressed by a thin-film transistor array. The mutual capacitance sensing nodes are configured to be passively matrix-addressed.

[0013] The device may further include the switches described herein. The device may also include a microcontroller unit (MCU) coupled to one of the plurality of ASICs. The MCU includes one or more processors and at least one tangible, non-transitory machine-readable medium configured to process the image data and / or control the operation of the device as described herein.

[0014] In another embodiment, the present invention provides a method using a device or system comprising a sensor having a pixel matrix containing two or more pixel arrays, the pixel arrays being logically divided into separate segments within the pixel matrix. This method includes the steps of: detecting the presence of an object having a biometric pattern on the sensor; performing a coarse scan (pre-scan) by scanning a portion of the pixels in the pixel array to determine a contact boundary between the object and the sensor; and selectively performing a detailed scan within the contact boundary to provide image data of the biometric pattern.

[0015] In some embodiments, the sensor is a fingerprint sensor, the object includes at least one finger, and the biometric pattern is a fingerprint.

[0016] As described herein, each pixel array includes a plurality of pixels arranged in a plurality of columns and a plurality of rows. These plurality of pixels include thermal sensing pixels. Each pixel array may further include a capacitive sensing grid having capacitive sensing nodes distributed throughout the pixel array.

[0017] In this method, the presence of an object (such as a finger touch) on the sensor is detected by thermal sensing pixels or capacitive sensing nodes. A coarse scan and a detailed scan are performed using the thermal sensing pixels.

[0018] The method may further include dynamically tracking the rolling motion and position of the object by capacitive scanning using one of the capacitive sensing nodes. The method may further include one or more steps of combining biometric images of the object captured by thermal scanning during the rolling motion of the object to provide a complete biometric pattern using the MCU.

[0019] In some embodiments, the capacitance sensing nodes are mutual capacitance sensing nodes or self-capacitance sensing nodes. The self-capacitance sensing nodes can be passively matrix-addressed or actively matrix-addressed by a thin-film transistor array. The mutual capacitance sensing nodes are configured for passive matrix addressing.

[0020] The sensors, devices, systems, and methods provided in this invention offer significant advantages that are not available in existing technologies. For example, the technologies provided in this invention offer faster scanning times, lower overall power consumption, improved image scanning bandwidth, the ability to scan a moving / rolling object (such as one or more fingers), and high resolution. For example, a large fingerprint sensor or system can be provided to meet the Fingerprint Acquisition Profile (FAP) standard. Simple Explanation of the Diagram

[0021] The invention will be better understood from the following detailed description when read in conjunction with the accompanying drawings. It should be emphasized that, by convention, the various features in the drawings are not necessarily drawn to scale. Instead, for clarity, the dimensions of the various features are arbitrarily enlarged or reduced. The same element symbols refer to the same features throughout the specification and drawings.

[0022] Figure 1 is a block diagram illustrating one of the exemplary systems (such as a biosensor system) according to some embodiments.

[0023] Figure 2 illustrates a schematic diagram of an exemplary sensor or device (such as a fingerprint sensor or device) according to one of some embodiments.

[0024] Figure 3 illustrates different contact areas of a rolling finger on a fingerprint sensor.

[0025] Figure 4A illustrates one of the pixel arrays in some embodiments.

[0026] Figures 4B and 4C illustrate two exemplary pixel matrices having a multi-segment sensing area and a pixel array according to some embodiments.

[0027] Figure 5A illustrates a device, such as a fingerprint sensor, having the pixel array of Figure 4A in some embodiments.

[0028] Figure 5B illustrates an exemplary device, such as a finger sensor, having (for example, as illustrated in Figure 4C) a multi-segment pixel matrix according to some embodiments.

[0029] Figure 6 illustrates an exemplary device, such as a finger sensor, having a multi-segment pixel matrix containing switches (e.g., illustrated in Figure 4C) according to some embodiments.

[0030] Figure 7 is a flowchart illustrating one method of selective active thermal scanning using an exemplary device (such as a finger sensor) having a multi-segment pixel matrix (or multiple pixel arrays) according to some embodiments.

[0031] Figures 8A to 8C illustrate a fingerprint in three steps according to some embodiments of the method from Figure 7, including finger detection (Figure 8A), rapid pre-scan (Figure 8B), and detailed fingerprint scanning (Figure 8C).

[0032] Figure 9 illustrates an exemplary sensor, such as a finger sensor, which has a multi-segment pixel matrix and a two-dimensional capacitive sensing grid with capacitive sensing nodes, according to some embodiments.

[0033] Figure 10 shows two examples of rectangular fingerprint scanning boundaries of a finger in an unrotated state (A) and a rotated state.

[0034] Figures 11A to 11C illustrate three instances of fingerprint scanning boundaries in the three steps of the method of Figure 7 according to some embodiments, including finger detection (Figure 11A), rapid pre-scan (Figure 11B), and detailed fingerprint scanning (Figure 11C).

[0035] Figure 12 illustrates one procedure for finger scrolling scanning operation using an exemplary system according to some embodiments.

[0036] Figure 13 illustrates one procedure for continuously capturing images of a rolling finger using an exemplary system according to some embodiments.

[0037] Figure 14 illustrates a procedure, according to some embodiments, of using an exemplary system to capture an image of a rolling finger with minimal image capture time to reduce total image scan power consumption.

[0038] Figure 15 is a flowchart illustrating one of the exemplary methods for biosensing according to some embodiments. Implementation

[0039] Priority claims and cross-references This application asserts the rights of U.S. Provisional Application No. 63 / 134,966, filed January 8, 2021, the entire contents of which are expressly incorporated herein by reference.

[0040] The description of this illustrative embodiment is intended to be read in conjunction with the accompanying drawings, which are considered an integral part of the written description. In the description, relative terms (such as "down," "up," "horizontal," "vertical," "above," "below," "upward," "downward," "top," and "bottom," and their extensions (e.g., "horizontally," "downward," "upward," etc.) should be interpreted as referring to the orientation described or shown in the figures in the discussion. These related terms are for ease of description and do not require the device to be constructed or operated in a particular orientation. Unless otherwise expressly stated, terms related to attachment, coupling, and the like (such as "connection" and "interconnection") refer to a relationship in which structures are directly or indirectly fixed or attached to each other through an intermediate structure, and movable or rigid attachments or relationships.

[0041] For the purposes of the following description, it should be understood that alternative variations and embodiments may be assumed. It should also be understood that the specific objects, compositions, and / or methods described herein are illustrative and should not be considered limiting.

[0042] In this invention, the singular forms "a" and "the" include plural references, and a reference to a particular numerical value at least includes that particular value, unless the context clearly indicates otherwise. When a value is expressed as an approximation, the use of the antecedent "about" will be understood to indicate that the particular value forms another embodiment. As used herein, "about X" (where X is a numerical value) preferably refers to ±10% (inclusive) of the value. For example, the phrase "about 8" preferably refers to a value of 7.2 to 8.8 (inclusive of 7.2 and 8.8). If present, all ranges are inclusive and combinable. For example, when a range of "1 to 5" is stated, the range should be interpreted as including ranges "1 to 4", "1 to 3", "1 to 2", "1 to 2 and 4 to 5", "1 to 3 and 5", "2 to 5", and the like. Furthermore, when a list of alternatives is actively provided, this list can be interpreted as meaning that any of the alternatives can be excluded, for example, by one of the negative limitations in the claims. For example, when a range of "1 to 5" is stated, the range can be interpreted to include situations that negatively exclude any of 1, 2, 3, 4, or 5; thus, a statement of "1 to 5" can be interpreted as "1 and 3 to 5, but not 2," or simply as "excluding 2." Any component, element, property, or step explicitly described herein is intended to be explicitly excluded from the scope of the patent application, whether such component, element, property, or step is listed as an alternative or described separately.

[0043] Unless otherwise expressly stated, the terms "connection" or "coupling" as used herein should be understood to cover different connections or couplings between or within components for conducting electricity or transmitting signals for communication. Such connections or couplings may be in wired, wireless, or cloud-based modes.

[0044] This invention provides a multi-segment pixel matrix, sensor or device, apparatus, system, and method for sensing (such as biosensing). The invention also provides a method, sensor, device, apparatus, and system for fabricating a multi-segment pixel matrix. For illustrative purposes only, the invention uses a finger as an illustrative object and a fingerprint as an example of a biometric pattern. Generally, the products and methods provided in this invention can be used to measure a pattern in a portion of a thermally conductive surface of an object. For example, this object may be the palm of a hand or skin in another part of the human body.

[0045] Large fingerprint sensing areas are highly desirable because they capture more fingerprint information in a single scan, providing higher recognition accuracy and lower false acceptance and false rejection rates. Simultaneously, high fingerprint scan resolution is necessary to obtain a high-quality fingerprint image that accurately captures fingerprint details, protrusion contours, and edge features. This detail is crucial for high-confidence fingerprint matching and enables anti-spoofing capabilities to distinguish between genuine and fake fingers. FBI-certified Personal Identity Authentication (PIV) and Image Quality Standards (IQS) require a small sensor resolution of 500 dpi. Both the large sensing area and high scan resolution necessitate that the implicit sensing system possess sufficiently high bandwidth to collect a complete fingerprint image from the large number of pixels on the sensor within a reasonable scan time.

[0046] Large fingerprint sensors capable of simultaneously scanning multiple fingers are becoming increasingly popular in consumer electronics and are becoming more important for law enforcement, border patrol, and other high-security applications. Specifically, the FAP60 fingerprint sensor, capable of simultaneously scanning four fingers and capturing a continuous fingerprint from a rolling finger, is the de facto standard for government offices, customs and immigration, and military applications. Therefore, to meet this growing demand, next-generation fingerprint sensors must possess extremely high image scanning and processing bandwidth capable of acquiring high-resolution fingerprint images from a large sensing area, recognizing multiple individual fingerprints, and dynamically acquiring fingerprints from a moving finger rolling across the sensor.

[0047] Active thermal imaging is one of the preferred solutions for implementing standard fingerprint sensors with large and high-resolution fingerprint capture profiles (FAP). It is inherently immune to sunlight interference and works well with wet or sweaty fingers. It offers a thinner, lighter, and more cost-effective alternative to optical counterparts. These features are highly anticipated for integration into mobile applications and wider adoption in consumer applications. By employing a novel sensing system architecture, the technology provided in this invention significantly improves scan bandwidth, scan time, and power consumption, enabling next-generation active thermal sensors to compete with optical sensors.

[0048] This invention employs selective active thermal sensing as the primary scanning method. Techniques described herein (such as multi-segment architectures) can also be used in sensors and systems that employ optical scanning as the primary scanning method.

[0049] In Figures 1 through 14, the same items are indicated by the same component symbols, and for the sake of brevity, the description of the structures provided above with reference to the previous figures is not repeated. The methods described in Figures 7 through 8 and Figures 11 through 15 refer to the illustrative structures described in Figures 1 through 6 and Figure 9.

[0050] Figure 1 is a schematic diagram of an exemplary system (such as a biosensor system 100) according to one of some embodiments. This exemplary system may be one possible architecture of a bioassay system.

[0051] Referring to Figure 1, in the embodiment illustrated, the biosensor system 100 includes a biometric (e.g., fingerprint) sensor 10, an image capture application-specific integrated circuit (“ASIC”) 50, and a microcontroller unit (“MCU”) 60. The ASIC 50 communicates with the biosensor 10 via an interface 11, and the MCU 60 communicates with the ASIC 50 via an interface 51. One or both of the ASIC 50 and the MCU 60 may be embedded in a single chip. The biosensor 10, under the control of the ASIC 50, is configured to capture an image of a biometric pattern (such as a fingerprint) and transmits the image data as a signal through the interface 11. In some embodiments, the biosensor 10 outputs an analog signal, and the interface 11 is an analog interface. The ASIC 50 may receive the analog signal and perform an analog-to-digital conversion (“A / D conversion”) before sending the image data to the MCU 60.

[0052] Alternatively, in some embodiments, the A / D conversion may occur within the fingerprint sensor 10, causing the biometric sensor 10 to output a digital signal and the interface 11 to be a digital interface. For example, in an embodiment where the biometric sensor 10 includes a pixel matrix (described below), each pixel may include an A / D converter and output a digital signal to the ASIC 50. In some embodiments, the fingerprint sensor 10 may output the digital signal directly to the MCU 60. The interface 11 also carries various other signals from the biometric sensor 10. The ASIC 50 and / or the MCU 60 may evaluate these signals to determine the presence and location of a sample on the biometric sensor 10. This information is used by the ASIC 50 and / or the MCU 60 to control scanning. For example, the ASIC 50 and / or the MCU 60 may identify a sub-section of the biometric sensor 10, and the ASIC 50 may instruct the biometric sensor 10 to scan only that sub-section.

[0053] An ASIC 50, serving as a processing chip, reads image data from the biosensor 10 and transmits it to the MCU 60 via an interface 51 (e.g., SPI, USB, or other suitable interface). The MCU 60 processes the image data based on so-called "details," extracts characteristic features, and generates a fingerprint template (e.g., an image of a fingerprint). In some embodiments, the MCU 60 has a fingerprint matching function that compares the fingerprint template with one or more stored fingerprints (e.g., fingerprints corresponding to authorized personnel) to determine whether the template matches any of the stored fingerprints. In some embodiments, the ASIC 50 and MCU 60 are components of an image capturing controller 70. In various embodiments, the image capturing controller 70 also includes one or more processors (not shown) that may be part of the biosensor system 100 integrated into one of the host systems (e.g., a smartphone, smart card, etc.).

[0054] In various embodiments, the functionality of the ASIC 50, MCU 60, image capture controller 70, and / or a smart card chip (not shown) can be integrated into a single chip or several chips within a host system. For example, the biometric sensor system 100 can be used in a mobile phone, a personal computer, an access control system, a USB reader, a point-of-sale terminal, a smart card, or any other suitable application. In some embodiments, such as for a smart credit card embodiment, a fingerprint template can be transferred to a smart card chip (integrated circuit card chip, ICC), where storage and matching are performed in a so-called on-card biometric comparison application (sometimes also referred to as "on-card matching" or "on-SE matching" (secure element)).

[0055] According to some embodiments, MCU 60 itself can be a controller of system 100 and is configured to control the operation of the entire fingerprint module or system 100. For example, the functionality of MCU 60 can range from detecting the presence of a finger, collecting or scanning a fingerprint to processing the image and encrypting the image to the host. Sometimes, the functionality of MCU 60 may depend on how much work a user expects to do in MCU 60. In some embodiments where "on-chip matching" is required, MCU 60 compares the collected fingerprint and determines whether it matches a fingerprint previously stored in MCU 60. In some embodiments, a user may expect MCU 60 to simply provide a complete image that will be "matched" in the host system (e.g., MSFT Windows Hello). However, in some other applications, a user may expect more control over the module operation and MCU 60 to be configured to execute in response to specific commands from the host.

[0056] Referring to Figures 1 and 2, in some embodiments, the fingerprint sensor 10 and the ASIC 50 may be mounted on a single substrate and referred to as a fingerprint sensor or a fingerprint sensing device 15. Figure 2 is a partial schematic diagram of an exemplary biometric (e.g., fingerprint) sensor or biometric (e.g., fingerprint) sensing device 15 in an exemplary system according to one of some embodiments. The MCU 60 may be housed within the biometric sensing device 15, or may be detached from the biometric sensing device when connected to it.

[0057] Referring to FIG2, in the embodiment illustrated therein, the biosensing device 15 includes a biosensor 10 (which includes a substrate 14), a pixel matrix 16 for the biosensor 10, circuitry 52, and connection points 53. The pixel matrix 16 may be one or more pixel arrays (i.e., a multi-segment pixel matrix or array) as described herein. In some embodiments, for example, as shown in FIG2, an ASIC 50 may be mounted to the substrate 14. In some embodiments, the biosensor 10 is a flexible sensor and the substrate 14 is a flexible material. In various embodiments, the substrate 14 may also be made of a polymer suitable for depositing microelectronic structures in manufacturing, a metal foil, a semiconductor material, quartz, glass, or any other material or a combination thereof. Examples of suitable polymer materials include (but are not limited to) polyethylene terephthalate (PET), polyethylene naphthalate, and polyimide. Examples of suitable metal foils include (but are not limited to) steel, aluminum, and a metal alloy. Examples of suitable semiconductor materials include (but are not limited to) silicon and group III to V semiconductor materials. In some embodiments, substrate 14 is made of a flexible material, such as polyimide and a metal foil.

[0058] As illustrated in Figure 2, the pixel matrix 16 is located on one surface of the substrate 14. In some embodiments, the pixel matrix 16 is formed on the surface of the substrate 14 using a thin-film transistor (TFT) fabrication process or other deposition process. For example, a low-temperature polysilicon (LTPS) fabrication process can be used. Connection point 53 is electrically coupled to the pixel matrix 16 via, for example, an ASIC 50 and allows connection to an external system, such as an MCU 60 (Figure 1). In some embodiments, a protective coating (not shown) may be applied to the pixel matrix 16. As will be further described herein, the surrounding circuitry 52 includes address lines that allow selective scanning or reading of specific columns or rows of the pixel matrix 16, or columns or rows within a specific region of the pixel matrix 16.

[0059] In various embodiments, the biosensor 10 operates based on the principle of active thermal sensing. In these embodiments, a low-power thermal pulse is applied to each sensor pixel within a short time period, and a response is measured. This type of fingerprint sensor can be manufactured through large-area production processes, such as those for forming LTPS thin-film transistors and devices. Based on the active thermal principle, the active thermal sensor measures the thermal conductivity of an object under a given thermal stimulus. Examples of active thermal sensing principles suitable for the present invention are disclosed in Dinh's U.S. Patent No. 6,091,837, entitled "Sensor for Acquiring a Fingerprint Image Based on Heat Transfer," and U.S. Patent No. 8,724,860, entitled "Apparatus for Fingerprint Sensing and Other Measurements," the entire contents of which are incorporated herein by reference. The response to the stimulus is measured by each sensing location within a sensor array. The thermal response of an element is a function of the stimulus provided; that is, the greater the stimulus, the greater the response. The sensing part is heated by applying an electric current to the part.

[0060] Because fingerprints have different thermal conductivity characteristics due to the varying skin structure, thermal sensors utilize heat transfer mechanisms to distinguish between fingerprint depressions and protrusions. A short thermal pulse is applied to selected pixels in a sensor array (or a portion of such an array as described herein), and heat exchange between the finger and the underlying individual sensors is monitored by measuring sensor temperature changes. A relatively high sensor temperature indicates that, due to lower thermal conductivity, there is minimal heat loss or exchange between the sensor in question and the finger. Points with low thermal conductivity map local fingerprint depressions, while points with high thermal conductivity (i.e., high thermal conductivity / transfer) map local fingerprint protrusions. Intermediate hot spots correspond to local transition zones between protrusions and depressions. Temperature differences are measured using sensing elements (e.g., fingerprint sensor pixels), and the measurements are processed to generate an image of the fingerprint on the fingerprint sensor.

[0061] The pixel arrays described herein include sensor elements or pixels 18, such as thermal sensing pixels 19 (illustrated in Figure 2). The pixel array may be a two-dimensional network of pixels 18. In some embodiments, the pixels or sensor elements may comprise one or more diodes connected in series between pixel columns. The diodes are close to the sensor surface and have good thermal contact with the fingerprint to be measured, and can function as both pixel heaters and temperature sensing elements.

[0062] The pixel heating power is proportional to the number of diodes and the product of a given current and voltage across each diode. Diodes are temperature sensitive, and if the current is biased, any temperature change in a pixel reflects a corresponding voltage change, or if the voltage is biased, it reflects a corresponding current change.

[0063] Pixel diodes can be any microelectronic device construction having pure or combined rectification characteristics. Suitable examples of diodes include (but are not limited to) a PN junction rectifier, a Schottky rectifier, a PIN diode, or any combination thereof. The diode can be made of a compound semiconductor (such as germanium or silicon) or a metal (such as aluminum) or organic material with suitable properties. The atomic structure can be single-crystal, amorphous, or polycrystalline.

[0064] The pixels may be covered with a conductive or semiconductor layer (not shown in the figure), which can be grounded to shield and protect the sensor. A protective coating (not shown in the figure) may be applied over the conductive or semiconductor layer to provide mechanical and chemical protection during use.

[0065] Table 1 summarizes the standard sensor specifications for fingerprint capture profiles (FAP) as defined in FBI specification PIV-071006 and Appendix F of the Electronic Biometrics Standard (EBTS). The total number of pixels in an FAP60 sensor is 20 times that of an FAP20 sensor. Therefore, the sensing bandwidth and processing power of the FAP60 must be scaled up proportionally to maintain a reasonable scan time.

[0066] Table 1 FAP20 FAP30 FAP40 / 45 FAP50 FAP60 unit Pixels 400 x 300 500 x 400 800 x 750 1600 x 1000 1600 x 1500 to 120K 200K 600,000 1600k 2400K Pixels Resolution 500 dpi size 0.8 x 0.6 1.0 x 0.8 1.6 x 1.5 3.2x2.0 3.2x3.0 inch 20.3 x 15.2 25.4 x 20.3 40.6 x 38.1 81.3 x 50.8 81.3 x 76.2 mm Active area 309.7 516.1 1548.4 4129.0 6193.5 mm 2 1 1.67 5.0 13.3 20.0 (normalization) Number of fingerprints 1 1 2 4 4 -

[0067] Another challenge for next-generation fingerprint sensors is capturing a continuous fingerprint from a rolling finger, as illustrated in Figure 3. As shown in Figure 3, from position (A), to (B), to (C), to (D), and then to (E), a finger 70 with a nail 71 rolls from one side of a sensor 10 to the other. The nail 71 is located on one side (i.e., the top side) of the finger 70, while the fingerprint is located opposite the finger 70. In position (C), the finger 70 is pressed against the sensor 10 with the largest contact area. Unlike a stationary finger, at any given moment, only a portion of the entire fingerprint is in contact with the sensor 10 available for image capture. The portions of the fingerprint from the rolling finger will only briefly contact the sensing surface, leaving a short window for proper capture of the moving fingerprint. This requires not only a high-bandwidth sensing system but also an intelligent sensing system to accurately locate and track finger movement to allocate available scanning resources to produce a high-quality fingerprint image.

[0068] This invention enables and provides a large-area fingerprint sensor that meets various FAP specifications (up to FAP60) by extending the sensing bandwidth based on the active thermal sensing principle.

[0069] According to some embodiments, an exemplary system 100 for biosensing includes a sensor 10 comprising a pixel matrix 16 having two or more pixel arrays (e.g., 36A, 36B, 36C, and 36D in Figures 4B-4C, 5B, and 6), the pixel arrays being logically divided into separate segments within the pixel matrix 16. A pixel matrix is ​​logically divided into multiple segments.

[0070] The term "logical partitioning" as used herein refers to rearranging or subdividing a pixel array (i.e., a full pixel array) into multiple segments (multiple pixel arrays) to facilitate image acquisition or image sensing. A user would not notice that there are no visual boundaries or physical gaps between the sub-partitions. In electrical engineering, "logical partitioning" typically refers to logically subdividing a larger task into several smaller tasks to improve performance, all of which can be processed consistently in the same manner.

[0071] Referring to Figure 4A, pixel matrix 16 contains a single pixel array 26.

[0072] Referring to Figures 4B and 4C, two exemplary pixel matrices 16 with a multi-segment image sensing and processing architecture are shown. As illustrated in Figures 4B to 4C, each pixel matrix 16 has multiple pixel arrays 36 logically divided within it. In Figure 4B, two pixel arrays 36 (A, B) are shown. In Figure 4C, four pixel arrays 36 (A, B, C, D) are shown. This novel sensor architecture is designed and configured to allow a large sensing area to be logically divided into multiple segments, and each individual pixel array (or segment) can be independently controlled by a corresponding driving circuit. The logical division does not affect pixel size or image resolution, and there are no physical gaps between adjacent segments. This partitioning allows multiple ASICs 50 to scan the active sensing area in parallel.

[0073] In some embodiments, the pixel matrix includes any suitable number of pixel arrays, such as from 2 to 12 pixel arrays, from 2 to 8 pixel arrays, from 2 to 6 pixel arrays, or from 2 to 4 pixel arrays. The number of pixel arrays (or segments) can be any integer in the range of 2 to 12. For example, the number of pixel arrays or segments can be 2, 3, 4, 5, 6, 7, or 8. The number of pixel arrays or segments is not limited by the algorithm used in the microcontroller, but may be limited by the physical implementation in device fabrication. For example, for some IC or TFT processes with only 2 to 3 metal layers, the number of pixel arrays may be lower, for example, from about 2 to about 4 pixel arrays. For example, for a process with 6 or more metal wiring layers, more pixel arrays, such as 8 or more arrays, can be easily supported.

[0074] As described in Figure 2, in some embodiments, each pixel array 36 includes a plurality of pixels disposed in a plurality of columns and a plurality of rows. Each pixel array may have its own invisible boundary. Each pixel array 36 includes thermal sensing pixels configured to operate based on an active thermal sensing principle, wherein a power thermal pulse is applied to each pixel array and the measurement corresponds to a response of a biometric pattern. For thermal sensing, a pixel in each pixel array may include one or more diodes connected in series between a pixel column line and a pixel row line.

[0075] Referring to Figures 5A to 5B, and also as described in Figures 1 to 2, the sensor or sensing device 15 includes at least one application-specific integrated circuit (ASIC) 50 and at least one support circuit 52.

[0076] Figure 5A illustrates an exemplary device 15 comprising a single pixel array 26. Figure 5B illustrates an exemplary sensor or device 15 comprising multiple pixel arrays 36. As shown in Figure 5B, the sensor or device 15 may further include a plurality of ASICs 50 (labeled 50A, 50B, 50C, and 50D) and a plurality of support circuits 52 (labeled 52A, 52B, ... 52H). Each pixel array 36 is connected to at least one support circuit 52. Each ASIC 50 is configured to capture image data of a biometric pattern of an object measured by at least one pixel array 36. Each pixel array 36 is configured to be driven and scanned independently by one or more of the plurality of ASICs 50. In Figure 5B, "Ckt" means "circuit". Sometimes, one ASIC 50 may be directed to scan an image across multiple pixel arrays 36. On the other hand, one pixel array 36 may be driven by multiple ASICs 50. Multiple (such as four different types) support circuits may exist around a pixel array to transmit input signals to the corresponding pixels during scanning and to collect analog data corresponding to an ASIC 50 to generate a fingerprint image. This circuitry is similar to the decoder and readout circuitry of SRAM or any memory product.

[0077] In some embodiments, each pixel array or segment 36 is driven and scanned by a separate ASIC (Figure 5B). If the active sensing area is logically divided into four segments, the four ASICs 50 are configured to operate in parallel. The image scanning bandwidth is increased by four times, and the time required to collect a complete image is approximately one-quarter of the original scanning time. In other words, the scanning time to collect a complete image is reduced to 1 / N of the original scanning time, where N is the number of segments.

[0078] Referring to Figure 6, in some embodiments, the sensor or device 15100 in the system may further include a plurality of switches 54 (e.g., labeled 54A, 54B, 54C, and 54D). The label "SW" in Figure 6 signifies a switch. Each switch 54 is connected to one or more support circuits 52 and one or more ASICs 50. Each pixel array 36 is configured to be independently driven and scanned by one or more of the plurality of ASICs 50 via one or more switches 54. In some embodiments, this switch 54 is an electronic contact switch. An electronic contact switch (e.g., a dual-gate MOSFET transistor) can be used to address and control signals from thermal sensing elements in a pixel array.

[0079] In some embodiments, a plurality of ASICs 50 and sensors 10 are housed together within a biosensing device 15. The sensors or devices 15 illustrated in Figures 5B and 6 are part of system 100. As described in Figure 1, system 100 may further include a microcontroller unit (MCU) 60 coupled to one of the plurality of ASICs 50. MCU 60 includes one or more processors and at least one tangible, non-transitory machine-readable medium configured to process image data and / or control the operation of the system using one or more program codes. In some embodiments, the number of ASICs may correspond to the number of pixel arrays. System 100 may contain only one MCU 60.

[0080] Using a switch 54, a user can select one ASIC 50 dedicated to each pixel array 36, or have multiple ASICs 50 process one pixel array 36 to improve scan speed and bandwidth. A powerful MCU 60 can be used to manage all ASICs 50, and the MCU 60 can determine how best to configure resources to minimize scan time, improve scan quality, or both.

[0081] Referring to Figure 6, in some embodiments, each pixel array segment 36 can be independently driven and scanned simultaneously by multiple ASICs 50. In the configuration shown in Figure 6, multiple ASICs 50 can operate together to simultaneously collect fingerprint images from the same pixel array segment 36. This configuration is particularly useful for collecting fingerprint images from one or more specific pixel array segments 36. Redirecting scanning resources to work in parallel can accelerate fingerprint scanning of specific local areas.

[0082] Compared to the size of a fingerprint, the FAP60 sensing area (81.3 × 76.2 mm) is much larger. Even for four-finger scanning, the fingerprint occupies only a small portion of the total sensing area. In most cases, the fingerprint covers less than 15% of the total sensing area.

[0083] In another embodiment, selective thermal scanning may be used in at least two steps. A coarse, low-resolution thermal scan is used to detect and locate the fingerprint, enabling a high-resolution thermal scan to capture an image only in the sensing area where the fingerprint is located. The sensing system intelligently selects the area of ​​interest for detailed fingerprint thermal scanning to significantly reduce thermal scanning activity rather than collecting a complete image from the entire sensing area. Therefore, scanning time and scanning energy consumption are proportionally reduced.

[0084] A scan resolution of 500 dpi or higher is considered high. 500 dpi is the standard for FBI FAP sensors used for fingerprint image capture. For example, a lower scan resolution could be 100 dpi or lower. The primary goal is to locate where a finger is or where the fingerprint boundary is so as not to waste time or effort scanning worthless areas.

[0085] System 100 is configured via MCU 60 to perform the functions and steps described herein. Referring to Figure 7, for example, an exemplary method 200 includes at least three steps. A first step is to detect the presence of an object having a biometric pattern on a sensor. A second step is to perform a coarse scan by scanning a portion of pixels in a pixel array to determine a contact boundary between the object and the sensor. A third step is to selectively perform a detailed scan within the contact boundary to provide image data of the biometric pattern.

[0086] Referring to Figure 7, during a standby mode, as shown in block 110, the sensing system 100 periodically performs an initial thermal scan (or a capacitive scan using the capacitive sensing grid described in Figure 9) at a low resolution to detect the presence of finger touches on the sensor. Only a small percentage (e.g., 2%) of pixels uniformly distributed across the sensor pixel array is selected for finger detection. Once a finger touch is detected and stable contact with the sensor is found (block 112), the system 100 proceeds to the next pre-scan (a coarse thermal scan) stage, selecting another set of pixels around the identified finger touch area to determine the fingerprint boundary (block 114). The system 100 may select a higher percentage (e.g., 8%) of pixels around the identified touch area to improve boundary calculation accuracy. Subsequently, as shown in block 116, a thermal scan with full resolution (i.e., a detailed thermal scan) is performed to collect a detailed fingerprint image within the identified boundary. The fingerprint scan area is only a small subset of the full pixel array.

[0087] Referring to Figure 8, an example of the steps in Figure 7 is further illustrated, including finger detection (Figure 8A), rapid pre-scan (Figure 8B), and detailed fingerprint scanning (Figure 8C). Fingerprint 72, touch area 74, and scanning area 76 are shown in Figures 8A to 8C.

[0088] By using method 200, the selective scanning method not only significantly improves image scanning and energy consumption, but also greatly reduces the computational effort and memory requirements of the subsequent 30 image processing steps.

[0089] By combining multi-segment sensing and selective thermal scanning, the image sensing bandwidth and processing power are more than an order of magnitude higher than conventional technologies. This significantly reduces the scanning time performance gap, enabling a fingerprint sensor to meet the requirements of the FAP60 sensor. At the same time, the lower image scanning power consumption makes it superior to similar products, such as existing optical technologies.

[0090] The steps in method 200 may also include steps for detecting rolling motion and position, combining images, and processing and comparing image data, as described in this invention.

[0091] In another approach, integrating capacitive scanning further enhances mobile applications of large fingerprint sensors to achieve ultra-low standby power consumption. Finger detection using coarse thermal scanning typically involves a trade-off between power consumption and detection response; more frequent finger detection improves system responsiveness, but standby power increases proportionally. Capacitive scanning operates faster and consumes less power than thermal scanning. Integrating capacitive scanning allows the sensing system to detect finger touches more frequently while maintaining very low standby power consumption. Furthermore, the projected capacitance field generated by each capacitive sensing node covers a wider area and a larger three-dimensional space than thermal scanning pixels. Proper placement of one capacitive sensing node can provide continuous and broader detection coverage across the entire pixel array. In addition to more frequent detection, capacitive scanning improves the accuracy and resolution of finger detection, representing a potentially more efficient solution with lower operating costs.

[0092] Referring to Figure 9, according to some embodiments, an exemplary sensor 10 also includes a capacitive sensing grid 78, which includes capacitive sensing nodes 78a distributed in each pixel array 36 or pixel matrix 16 (illustrated as dots in Figure 9). The lines in Figure 9 represent pixel arrays 36 used for thermal scanning. The system or device may further include auxiliary circuitry (not shown) for the capacitive sensing grid 78 in a respective ASIC or MCU. The auxiliary circuitry may also be a separate IC external to the respective ASIC or MCU. The capacitive sensing grid 78 is connected to the auxiliary circuitry. To achieve a capacitive scan, as illustrated in Figure 9, a two-dimensional grid of capacitive sensing nodes 78a across the active sensing region is integrated into the fingerprint sensor 10. The grid sensing nodes 78a of the capacitive sensor are coarser than the pixel array 36 having sensing pixels 19. The grid 78 may be implemented in each pixel array 36 or in the pixel matrix 16.

[0093] Thanks to improved detection accuracy and resolution, fast capacitive scanning can not only be used to identify the presence of a finger on the sensor in standby mode, but also to more accurately locate the position and estimate the size of each finger's touch. Once the finger is in stable contact with the sensor, the system will run a coarse thermal scan (fast pre-scan) to confirm the presence of the finger and calculate the appropriate fingerprint boundaries.

[0094] In some embodiments, the two-dimensional grid of the capacitive sensing node can be implemented using mutual capacitance sensing with X transmitting electrodes (Tx) and Y receiving electrodes (Rx). Passive matrix addressing mutual capacitance scanning supports multi-touch functionality and is relatively inexpensive. The Tx and Rx electrodes can be embedded in the fingerprint sensor and are uniformly distributed on the pixel array. In one example, the Tx electrodes are uniformly distributed on the long side of the pixel array, with K pixels between two adjacent electrodes. The Rx electrodes are uniformly distributed on the short side of the pixel array, with M pixels between two adjacent electrodes. K and M are adjustable numbers based on product resolution and other performance specifications. In another example, the Tx electrodes are uniformly distributed on the short side of the pixel array and the Rx electrodes are uniformly distributed on the long side of the pixel array.

[0095] In another embodiment, the two-dimensional grid 78 of the capacitive sensing node is implemented using active matrix addressing self-capacitive sensing. Compared to mutual capacitance sensing, self-capacitive sensing offers higher sensitivity and higher touch resolution, but requires more signal routing and implementation overhead to implement self-capacitive sensing nodes.

[0096] Selective thermal scanning not only significantly reduces the fingerprint scanning area but also allows the sensing system to determine a customized fingerprint boundary for each finger to optimize scanning coverage and further reduce unnecessary scanning activity. Using a large sensor like the FAP60, the fingerprint can enter at any angle as long as it is within the sensing area. The fingerprint can rotate within the sensing area, or the fingers can be oriented differently.

[0097] As shown in Figure 10, the two fingerprints are identical to the fingerprint rotated 45° on the right. To cover the entire fingerprint, the rectangular scanning boundary of the rotated fingerprint requires approximately 25% larger scanning area compared to the unrotated fingerprint, proportionally scanning more empty pixels to increase scanning time and energy consumption.

[0098] The use of capacitive scanning significantly improves the accuracy of finger touch position and size estimation. Therefore, rapid pre-scanning can better rely on finger information collected from capacitive scanning and strategically select a small number of thermally sensing pixels around the projected fingerprint perimeter for subsequent detailed fingerprint thermal scanning calculations to obtain a more accurate and customized fingerprint profile. Instead of using a fixed-size or rectangular boundary 76, the scan boundary 74 can be irregular and adjusted for each detected fingerprint 72, as illustrated in Figures 11A to 11C. This further minimizes unnecessary scanning activity on non-contact or unoccupied pixels, which helps maintain a more consistent scan time between rotated and non-rotated fingers.

[0099] In another embodiment, the present invention provides a sensor or device 15 for biometric sensing, as described herein. This device 15 includes a sensor 10 of a pixel matrix 16 having two or more pixel arrays 36 as separate segments logically divided within the pixel matrix 16, and a plurality of ASICs 50 coupled to the sensor 10. Each ASIC 50 is configured to capture image data of a biometric pattern of an object measured by at least one pixel array 36. Each pixel array 36 is configured to be independently driven and scanned by one or more of the plurality of ASICs 50. In some embodiments, the sensor 10 is a fingerprint sensor, the object is a finger 70, and the biometric pattern is a fingerprint 72.

[0100] In some embodiments, each pixel array 36 includes a plurality of pixels disposed in a plurality of columns and a plurality of rows, and the plurality of pixels includes thermal sensing pixels. Each pixel array may further include a capacitance sensing grid 78, which includes capacitance sensing nodes 78a distributed in each pixel array 36. The capacitance sensing grid 78 is configured to detect the presence of an object and / or the rolling motion and position of the object. The capacitance sensing nodes 78a may be mutual capacitance sensing nodes or self-capacitance sensing nodes. Self-capacitance sensing nodes are configured to be passively matrix-addressed or actively matrix-addressed by a thin-film transistor array. Mutual capacitance sensing nodes are configured to be passively matrix-addressed.

[0101] Device 15 may further include the switches described herein. Device 15 may also include a microcontroller unit (MCU) 60 coupled to one of a plurality of ASICs 50. MCU 60 includes one or more processors and at least one tangible, non-transitory machine-readable medium configured to process image data and / or control the operation of devices as described herein.

[0102] Table 2 summarizes the results of a four-finger test case study using experimental examples (FAP 60 sensor) based on some embodiments. The FAP60 active sensing system uses a multi-segment architecture to divide the region logic into 8 segments, each driven and scanned by a single ASIC. Due to segmented parallel scanning, the full image scan time is significantly reduced from 13.8 seconds to 1.73 seconds, 8 times faster than conventional solutions. With selective thermal scanning enabled, scanning only the fingerprint area further reduces the scan time to 0.67 seconds, approximately 2.5 times faster. Pre-scanning requires additional time for boundary assessment and image processing, but this overhead is much smaller compared to the time saved by scanning detailed fingerprint images. In addition, the total image scan power consumption is approximately 5 times. Disabling sensor pixel array segments without finger touch and activating only the sensor pixels that the fingerprint is in contact with significantly reduces image scanning and processing activities. Further enabling the customer scan boundary function allows the scan boundary to bypass non-contact pixels and more closely surround each fingerprint contour, saving additional scan time and power consumption. By implementing these novel features, test case studies have shown that scan time is reduced by more than 20 times, while energy consumption is reduced by nearly 6 times.

[0103] Table 2 Scan time Energy consumption estimate normalization estimate normalization Known architecture (single pixel array) 13.8 seconds 22.6 577 mJ 5.84 - Multi-segment architecture (8 segments) 1.73 seconds 2.83 577 mJ 5.84 - Multi-segment architecture (8 segments)+ -Selective thermal scanning (w / capacitance scanning) 0.67 seconds 1.10 109 mJ 1.10 - Multi-segment architecture (8 segments)+ -Selective thermal scanning (w / capacitance scanning)+ -Custom scan boundary 0.61 seconds 1 98.8 mJ 1

[0104] As shown in Table 2, the performance improvement using a multi-segment architecture is significant compared to a single-pixel array, including faster scan times and lower overall power consumption. Image scan time can be reduced from 13.8 seconds to 0.61 seconds (more than 20 times faster), while power consumption is reduced by nearly 6 times. These are huge performance improvements. Due to the greatly improved image scan bandwidth, it is even possible to scan a moving / scrolling finger. This will enable new product features that we cannot currently support.

[0105] In addition to improved finger touch assessment, the interoperability between capacitive and thermal scanning enables the sensing system to support finger-scrolling scanning to capture fingerprints in a short time. The integration of fast capacitive scanning allows the sensing system to dynamically track finger movement, dynamically determine the correct thermal scan boundary, and optimize fingerprint scanning operations as the finger rolls across the sensing area for fingerprint capture. In other words, it provides the functionality necessary for a smart sensing system that utilizes available scanning resources to capture continuously rolling fingerprints.

[0106] Figure 12 illustrates an example of operation using self-capacitance sensing to implement capacitive sensing nodes 78. The touch value detected by each capacitive sensing node 78 changes as a finger 70 rolls across the sensing area. The touch value increases as the finger approaches, remains constant if in full contact, and decreases as the finger rolls away. By continuously monitoring the touch value, the sensing system can accurately locate the moving finger 70 at any given moment. Instead of scanning from an arbitrary starting point, the example sensing system 100 can locate the corresponding portion of the pixel array 36 where the rolling finger 70 is currently positioned, and select a smaller subset of pixels currently in contact with the finger 70 to collect detailed fingerprint images. In Figure 12, unscanned thermal pixels 80, scanned thermal pixels 82, and actively scanned thermal pixels 84 of the pixel array 36 in the sensor 10 are illustrated. Using this finger tracking function, thermal scanning can be better aligned with the rolling finger in time, position, and contact area (scan size) to optimize image scan quality and bandwidth.

[0107] One technique for improving image quality and signal-to-noise ratio (SNR) involves averaging multiple images of the same fingerprint area to produce a final image. In some embodiments, due to higher image scanning bandwidth, the sensing system 100 can be configured to continuously capture the rolling fingerprint 70 on the sensor 10, capturing the same printed area multiple times in a continuous scan as illustrated in FIG. 13. The images are then combined in an image processing procedure to produce a complete rolling fingerprint, and the copied portions are averaged to improve image quality and SNR. In FIG. 13, the number of scans (9) is for illustration only and can be any suitable number.

[0108] In some embodiments, the sensing system 100 can be configured to minimize repeated image capture to reduce total image scanning power consumption. For example, the sensing system 100 can be configured such that, as illustrated in FIG14, any given fingerprint region is scanned only once. This minimizes the total number of scans and scanning activities to save power. For example, as illustrated in FIGS13 and 14, the total number of scans can be reduced from 9 to 5. The optimal total number of scans for each rolling finger can be in the range of 3 to 7.

[0109] Referring to Figure 15, as described above, an exemplary method 200 for biosensing according to some embodiments is generally described. Method 200 is used with a device or system including an exemplary sensor 10. This sensor 10 includes a pixel matrix 16 having two or more pixel arrays 36, the pixel arrays being logically divided into separate segments within the pixel matrix 16. This method 200 includes steps 202, 204, and 206.

[0110] In step 202, the presence of an object having a biometric pattern is detected on sensor 10. In some embodiments, sensor 10 is a fingerprint sensor, the object includes at least one finger 70, and the biometric pattern is a fingerprint 72. As described herein, the sensor has a pixel matrix 16 having a plurality of segments. Each pixel array 36 includes a plurality of pixels arranged in a plurality of columns and a plurality of rows. The plurality of pixels 18 includes thermal sensing pixels 19. Each pixel array 36 may further include a capacitive sensing grid 78 having capacitive sensing nodes distributed in each pixel array.

[0111] In step 204, a coarse scan (a pre-scan) is performed by scanning a portion of the pixels in a pixel array to determine a contact boundary between the object and the sensor. In this method, the presence of an object (such as a finger 70) on the touch sensor 10 is detected by thermal sensing pixels 19 or capacitive sensing nodes 78. Coarse and detailed scans are performed using thermal sensing pixels.

[0112] In step 206, a detailed scan is selectively performed within the contact boundary to provide image data of the bioassay pattern.

[0113] In step 208, as described in Figures 12 to 14, the rolling motion and position of the object are dynamically tracked by capacitive scanning using one of the capacitive sensing nodes 78. In some embodiments, the capacitive sensing node 78 is a mutual capacitance sensing node or a self-capacitance sensing node. The self-capacitance sensing node can be passively matrix-addressed or actively matrix-addressed by a thin-film transistor array. The mutual capacitance sensing node is configured to be passively matrix-addressed.

[0114] In step 210, the MCU is used to combine the object biometric images captured by thermal scanning during the object's rolling motion to provide a complete biometric pattern. Step 210 may include one or more steps.

[0115] The present invention provides at least the products and methods described in the following clauses, which are merely examples and do not limit the scope of the present invention. 1. A system for biosensing, comprising: A sensor comprising a pixel matrix having two or more pixel arrays as one of the independent segments logically divided within the pixel matrix; A plurality of application-specific integrated circuits (ASICs) coupled to the sensor, wherein each ASIC is configured to capture image data of a biometric pattern of an object measured by at least one pixel array, and each pixel array is configured to be independently driven and scanned by one or more of the plurality of ASICs; and A microcontroller unit (MCU) coupled to the plurality of ASICs and including one or more processors and at least one tangible, non-transitory machine-readable medium configured to process the image data and / or control the operation of the system. 2. The system of clause 1, wherein the pixel matrix comprises an array of from 2 to about 12 pixels. 3. The system of items 1 to 2, wherein the plurality of ASICs and the sensor are housed together in a biosensing device. 4. The system of any one of items 1 to 3, wherein the sensor further includes a plurality of support circuits, wherein each pixel array is connected to at least one support circuit. 5. The system of any one of items 1 to 4 further includes a plurality of switches, wherein each pixel array is configured to be independently driven and scanned by one or more of the plurality of ASICs through one or more switches. 6. A system as described in any of items 1 to 5, wherein each pixel array comprises a plurality of pixels arranged in a plurality of columns and a plurality of rows. 7. A system as described in any of clauses 1 to 6, wherein each pixel array includes thermally sensing pixels configured to operate based on an active thermal sensing principle, wherein a power thermal pulse is applied to each pixel array and the measurement corresponds to a response of a biometric pattern. 8. A system as described in any of items 1 to 7, wherein one pixel in each pixel array comprises one or more diodes connected in series between a pixel column line and a pixel row line. 9. The system of any one of items 1 to 8, wherein each pixel array further includes a capacitive sensing grid having capacitive sensing nodes distributed in each pixel array. 10. The system of clause 9 further includes an auxiliary circuit as an independent integrated circuit in or outside of a respective ASIC or MCU, wherein the capacitive sensing grid is connected to the auxiliary circuit. 11. A system as described in any of items 1 to 9, wherein the system is configured to perform the following steps via the MCU: Detects the presence of one of the objects on the sensor that has a biometric pattern; A coarse scan is performed by scanning a portion of the pixels in a pixel array to determine a contact boundary between the object and the sensor; and A detailed scan is selectively performed within the contact boundary to provide image data of the bioassay pattern. 12. A device for biosensing, comprising: A sensor comprising a pixel matrix having one of two or more pixel arrays, the pixel arrays being logically divided into separate segments within the pixel matrix; and A plurality of application-specific integrated circuits (ASICs) are coupled to the sensor, wherein each ASIC is configured to capture image data of a biometric pattern of an object measured by at least one pixel array, and each pixel array is configured to be independently driven and scanned by one or more of the plurality of ASICs. 13. The device of clause 12, wherein the sensor is a fingerprint sensor, the object is a finger, and the biometric pattern is a fingerprint. 14. The device of any one of items 12 to 13, wherein each pixel array includes a plurality of pixels arranged in a plurality of columns and a plurality of rows, and the plurality of pixels includes thermal sensing pixels. 15. The device of any one of clauses 12 to 14, wherein each pixel array further includes a capacitive sensing grid having capacitive sensing nodes distributed in each pixel array and configured to detect the presence of an object and / or the rolling motion and position of the object. 16. The device of any of clauses 15, wherein the capacitance sensing nodes are mutual capacitance sensing nodes or self-capacitance sensing nodes. 17. The device of any one of clauses 15 to 16, wherein the self-capacitance sensing nodes are configured to be passively matrix-addressed or actively matrix-addressed by a thin-film transistor array. 18. The device of any one of items 15 to 16, wherein the mutual capacitance sensing nodes are configured to be passively matrix addressed. 19. The device of any one of clauses 12 to 18 further includes a microcontroller unit (MCU) coupled to the plurality of ASICs and including the MCU, comprising one or more processors and at least one tangible, non-transitory machine-readable medium configured to process the image data and / or control the operation of the device. 20. A method of using a device or system, the device or system including a sensor having a pixel matrix comprising two or more pixel arrays, the pixel arrays being logically divided into separate segments within the pixel matrix, the method comprising the steps of: Detects the presence of one of the objects on the sensor that has a biometric pattern; A coarse scan is performed by scanning a portion of the pixels in a pixel array to determine a contact boundary between the object and the sensor; and A detailed scan is selectively performed within the contact boundary to provide image data of the bioassay pattern. 21. The method of clause 20, wherein the sensor is a fingerprint sensor, the object includes at least one finger, and the biometric pattern is a fingerprint. 22. The method of any one of clauses 20 to 21, wherein each pixel array includes a plurality of pixels disposed in a plurality of columns and a plurality of rows, the plurality of pixels including thermal sensing pixels, and each pixel array further includes a capacitive sensing grid having capacitive sensing nodes distributed in the pixel array. 23. The method of clause 22, wherein the presence of an object on the sensor is detected by means of the thermal sensing pixels or the capacitive sensing nodes. 24. The method of any one of clauses 22 to 23, wherein the coarse scan and the detailed scan are performed through the thermal sensing pixels. 25. The method of any one of clauses 22 to 24, further comprising dynamically tracking the rolling motion and position of the object by using one of the capacitive sensing nodes for capacitive scanning. 26. The method of any one of 21 to 25, further comprising combining biometric images of the object captured by thermal scanning during the rolling motion of the object to provide a complete biometric pattern using the MCU. 27. The method of any one of clauses 22 to 26, wherein the capacitance sensing nodes are mutual capacitance sensing nodes or self-capacitance sensing nodes. 28. The method of any one of clauses 22 to 27, wherein the self-capacitance sensing nodes may be passively matrix-addressed or actively matrix-addressed by a thin-film transistor array; and the mutual capacitance sensing nodes are configured to be passively matrix-addressed.

[0116] The sensors, devices, systems, and methods provided in this invention offer significant advantages that are not available in existing technologies. For example, the technologies provided in this invention offer faster scanning times, lower overall power consumption, improved image scanning bandwidth, the ability to scan a moving / rolling object (such as one or more fingers), and high resolution. For example, a large fingerprint sensor or system can be provided to meet the Fingerprint Acquisition Profile (FAP) standard.

[0117] The methods and systems described herein can be embodied, at least in part, in the form of computer-implemented programs and apparatus for implementing such programs. The disclosed methods can also be embodied, at least in part, in the form of tangible, non-transitory machine-readable storage media encoded using computer program code. The media may include, for example, RAM, ROM, CD-ROM, DVD-ROM, BD-ROM, hard disk drive, flash memory, or any other non-transitory machine-readable storage media, or any combination of such media, wherein when the computer program code is loaded into and executed by a computer, the computer becomes an apparatus for practicing the method. The method can also be embodied, at least in part, in the form of a computer in which computer program code is loaded and / or executed, making the computer an apparatus for practicing the method. When implemented on a general-purpose processor, the computer program code fragments configure the processor to insert specific logic circuitry. Alternatively, the method can be embodied, at least in part, in a digital signal processor formed by application-specific integrated circuitry for performing the method.

[0118] Although the subject matter has been described with reference to exemplary embodiments, it is not limited thereto. Rather, the appended claims should be interpreted broadly to include other variations and embodiments that may be made by those skilled in the art.

[0119] 10: Sensors 11: Interface 14:Substrate 15: Fingerprint sensing devices / biometric sensing devices 16: Pixel Matrix 18: pixels 19: Thermal sensing pixels 26: pixel array 36: pixel array 36A: Pixel Array 36B: Pixel Array 36C: Pixel Array 36D: Pixel Array 50: Application-Specific Integrated Circuits (ASICs) 50A: Application Specific Integrated Circuit (ASIC) 50B: Application-Specific Integrated Circuit (ASIC) 50C: Application Specific Integrated Circuit (ASIC) 50D: Application Specific Integrated Circuit (ASIC) 51: Interface 52: Support circuit 52A to 52H: Support circuits 53: Connection Point 54: Switch 54A: Switch 54B: Switch 54C: Switch 54D: Switch 60: Microcontroller Unit (MCU) 70: Image capturing controller / finger 71: Fingernails 72: Fingerprint 74: Touch Area 76: Scanning area 78: Capacitive sensing grid 78a: Capacitive sensing node 80: Unscanned thermal pixels 82: Scanning thermal pixels 84: Active scanning thermal pixels 100: Biosensor System 110: Block 112: Block 114: Block 116: Block 200: Method 202: Steps 204: Steps 206: Steps 208: Steps 210: Steps

Claims

1. A system for biosensing, comprising: A sensor comprising a pixel matrix having two or more pixel arrays as logically divided independent segments within the pixel matrix, wherein the pixel matrix is ​​a single and continuous pixel matrix, and the sensor being a biosensor configured to measure a biometric pattern of skin in a part of a human body by means of at least one pixel array; a plurality of application-specific integrated circuits (ASICs) coupled to the sensor, wherein each ASIC is configured to capture image data of a biometric pattern of an object measured by at least one pixel array, and each pixel array is configured to be independently driven and scanned by one or more of the plurality of ASICs; and a microcontroller unit (MCU) coupled to the plurality of ASICs and including one or more processors and at least one tangible, non-transitory machine-readable medium configured to process the image data and / or control the operation of the system.

2. The system of claim 1, wherein the pixel matrix comprises an array of from 2 to about 12 pixels.

3. The system of claim 1, wherein the plurality of ASICs and the sensor are housed together in a biosensing device.

4. The system of claim 1, wherein the sensor further includes a plurality of support circuits, wherein each pixel array is connected to at least one support circuit.

5. The system of claim 1, further comprising a plurality of switches, wherein each pixel array is configured to be independently driven and scanned by one or more of the plurality of ASICs via one or more switches.

6. The system of claim 1, wherein each pixel array comprises a plurality of pixels arranged in a plurality of columns and a plurality of rows.

7. The system of claim 1, wherein each pixel array includes thermal sensing pixels and is configured to operate based on an active thermal sensing principle, wherein a power thermal pulse is applied to each pixel array and the measurement corresponds to a response of a biometric pattern.

8. The system of claim 7, wherein one pixel in each pixel array comprises one or more diodes connected in series between a pixel column line and a pixel row line.

9. The system of claim 7, wherein each pixel array further includes a capacitive sensing grid having capacitive sensing nodes distributed in each pixel array.

10. The system of claim 9, further comprising an auxiliary circuit as an independent integrated circuit in or outside of a respective ASIC or MCU, wherein the capacitive sensing grid is connected to the auxiliary circuit.

11. The system of claim 1, wherein the MCU is configured to perform the following steps: detecting the presence of an object having a biometric pattern on the sensor; performing a coarse scan by scanning a portion of pixels in a pixel array to determine a contact boundary between the object and the sensor; and selectively performing a detailed scan within the contact boundary to provide image data of the biometric pattern.

12. The system of request item 1, wherein the part of the human body is a hand.

13. A device for biosensing, comprising: A sensor includes a pixel matrix having one of two or more pixel arrays, the pixel arrays being logically divided into separate segments within the pixel matrix, wherein the pixel matrix is ​​a single and continuous pixel matrix, and the sensor is a biosensor configured to measure a biometric pattern of skin in a part of a human body by means of at least one pixel array; and a plurality of application-specific integrated circuits (ASICs) coupled to the sensor, wherein each ASIC is configured to capture image data of a biometric pattern of an object measured by at least one pixel array, and each pixel array is configured to be independently driven and scanned by one or more of the plurality of ASICs.

14. The device of claim 13, wherein the sensor is a fingerprint sensor, the object is a finger, and the biometric pattern is a fingerprint.

15. The device of claim 13, wherein each pixel array includes a plurality of pixels disposed in a plurality of columns and a plurality of rows, and the plurality of pixels includes thermal sensing pixels.

16. The device of claim 15, wherein each pixel array further includes a capacitive sensing grid having capacitive sensing nodes distributed in each pixel array and configured to detect the presence of an object and / or the rolling motion and position of the object.

17. The device of claim 16, wherein the capacitance sensing nodes are mutual capacitance sensing nodes or self-capacitance sensing nodes.

18. The device of claim 17, wherein the self-capacitance sensing nodes are configured to be passively matrix-addressed or actively matrix-addressed by a thin-film transistor array.

19. The device of claim 17, wherein the mutual capacitance sensing nodes are configured to be passively matrix-addressed.

20. The device of claim 13 further includes a microcontroller unit (MCU) coupled to the plurality of ASICs and including one or more processors, and at least one tangible, non-transitory machine-readable medium using one or more program codes configured to process the image data and / or control the operation of the device.

21. The device as claimed in claim 13, wherein the part of the human body is a hand.

22. A method of using a device or system comprising a sensor having a pixel matrix containing two or more pixel arrays, the pixel arrays being logically divided separate segments within the pixel matrix, the method comprising the steps of: detecting the presence of an object having a biometric pattern on the sensor; performing a coarse scan by scanning a portion of the pixels in the pixel arrays to determine a contact boundary between the object and the sensor; and selectively performing a detailed scan within the contact boundary to provide image data of the biometric pattern, wherein the pixel matrix is ​​a single and continuous pixel matrix, wherein each pixel array includes active thermal sensing pixels and is configured to operate based on an active thermal sensing principle, wherein a power thermal pulse is applied to each pixel array and measures a response corresponding to the biometric pattern, wherein each pixel array is independently driven and scanned by one or more of a plurality of application-specific integrated circuits (ASICs) connected to the sensor, and wherein the sensor is a biosensor configured to measure the biometric pattern, and the object is a portion of human skin.

23. The method of claim 22, wherein the sensor is a fingerprint sensor, the object includes at least one finger, and the biometric pattern is a fingerprint.

24. The method of claim 22, wherein each pixel array includes a plurality of pixels disposed in a plurality of columns and a plurality of rows, the plurality of pixels including thermal sensing pixels, and each pixel array further includes a capacitive sensing grid having capacitive sensing nodes distributed in the pixel array.

25. The method of claim 24, wherein the presence of an object on the sensor is detected by means of the thermal sensing pixels or the capacitive sensing nodes.

26. The method of claim 24, wherein the coarse scan and the detailed scan are performed through the thermal sensing pixels.

27. The method of claim 24 further includes dynamically tracking the rolling motion and position of the object by using one of the capacitive sensing nodes for capacitive scanning.

28. The method of claim 27, further comprising combining biometric images of the object captured by thermal scanning during the rolling motion of the object to provide a complete biometric pattern using an MCU.

29. The method of claim 24, wherein the capacitance sensing nodes are mutual capacitance sensing nodes or self-capacitance sensing nodes.

30. The method of claim 24, wherein the self-capacitance sensing nodes may be passively matrix-addressed or actively matrix-addressed by a thin-film transistor array; and the mutual capacitance sensing nodes are configured to be passively matrix-addressed.

31. The method of claim 22, wherein the part of the human body is a hand.

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