Patent Publication Number: US-2022222964-A1

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

Description:
PRIORITY CLAIM AND CROSS-REFERENCE 
     This application claims the benefit of U.S. Provisional Application No. 63/134,966, filed Jan. 8, 2021, which application is expressly incorporated by reference herein in its entirety. 
    
    
     FIELD OF THE INVENTION 
     The disclosure relates to a device or apparatus and a method for measuring patterns in a partially heat conducting surface generally. More particularly, the disclosed subject matter relates to a device or apparatus for biometric sensing such as a fingerprint sensor, a system, and a method for measuring or capturing an image of a biometric (e.g., fingerprint) pattern. 
     BACKGROUND 
     Fingerprint sensors are one form of technology used to provide biometric security. The fine patterns formed by ridges and valleys on the finger&#39;s skin can be mapped by sensing arrays, which vary in basic operating principles. Some sensors utilize heat signals, while others utilize electrical, pressure, or optical signals. Active sensors quantify a specific physical parameter response to a given stimulus. Accuracy levels are limited by the physical principles used to read fingerprint patterns. Furthermore, immunity to environmental variables such as dirt or humidity is also important when performing a fingerprint scan. 
     Fingerprint sensors are often used in electronic devices to verify the identity of the user and to restrict access unless the sensor verifies that an authorized user is attempting to use the device. For example, certain smart credit cards require verification of the user via a fingerprint sensor before use. Fingerprint sensors are also included in computing devices—such as smartphones, tablet computers, laptops, and point of sale devices—to ensure that only authorized users are able to unlock and use such devices. 
     SUMMARY OF THE INVENTION 
     The present disclosure provides a multi-segment pixel matrix, a sensor or device, a system, and a method, for biometric sensing. 
     In accordance with some embodiments, a system for biometric sensing comprises a sensor, which comprises a pixel matrix having two or more pixel arrays as separate segments logically divided in the pixel matrix. The system further comprises a plurality of application-specific intergrade 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 the ASICs. The system may further comprise a microcontroller unit (MCU) coupled to the plurality of ASICs. The MCU comprises one or more processor and at least one tangible, non-transitory machine readable medium encoded with one or more programs configured to process the image data and/or control operation of the system. In some embodiments, the plurality of ASICs and the sensor are disposed together within a biometric sensing device. 
     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 the pixel arrays (or segments) can be any integer in a range of from 2 to 12. 
     The sensor may further comprise a plurality of supporting circuits. Each pixel array is connected with at least one supporting circuit. In some embodiments, the sensor in the system may further comprise a plurality of switches. Each switch is connected with one or more supporting 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 the ASICs through one or more switches. 
     In some embodiments, each pixel array comprises a plurality of pixels arranged in a plurality of rows and a plurality of columns. Each pixel array comprises thermal sensing pixels, which are configured to operate based on the active thermal sensing principle, in which a power heat pulse is applied to each pixel array and a response corresponding to a biometric pattern is measured. For thermal sensing, a pixel in each pixel array may comprise one or more diodes connected in series between a pixel row line and a pixel column line. 
     In accordance with some embodiments, each pixel array further comprises a capacitive sensing grid comprising capacitive sensing nodes distributed in each pixel array. The system or device may further comprise an auxiliary circuit for the capacitive sensing grid in a respective ASIC or in the MCU or outside the respective ASIC or the MCU as an independent integrated circuit. The capacitive sensing grid is connected with the auxiliary circuit. 
     Through the MCU, the system is configured to perform the functions and steps as described herein. For example, the steps comprise: detecting a presence of an object having a biometric pattern on the sensor, performing a coarse scan by scanning a fraction of pixels in a pixel array to determine a contact boundary between the object and the sensor, and performing a detailed scan selectively within the contact boundary to provide the image data of the biometric pattern. The steps may also include those for detecting rolling motion and location, combining images, and processing and comparing image data as described in the present disclosure. 
     In another aspect, the present disclosure provides a sensor or device for biometric sensing. Such a device comprises a sensor comprising a pixel matrix having two or more pixel arrays as separate segments logically divided in the pixel matrix, and a plurality of application-specific intergrade 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 the ASICs. In some embodiments, the sensor is a fingerprint sensor, the object is a finger, and the biometric pattern is a fingerprint. 
     In some embodiments, each pixel array comprises a plurality of pixels arranged in a plurality of rows and a plurality of columns, and the plurality of pixels comprise thermal sensing pixels. Each pixel array may further comprise a capacitive sensing grid comprising capacitive sensing nodes distributed in each pixel array. The capacitive sensing grid is configured to detect a presence of the object, and/or rolling motion and location 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 passive-matrix addressed, or active-matrix addressed by an array of thin film transistors. The mutual capacitance sensing nodes are configured to be passive-matrix addressed. 
     The device may further comprise the switches as described herein. The device may also comprise a microcontroller unit (MCU) coupled to the plurality of ASICs. The MCU comprises one or more processor and at least one tangible, non-transitory machine readable medium encoded with one or more programs configured to process the image data and/or control operation of the device as described herein. 
     In another aspect, the present disclosure provides a method of using a device or a system comprising a sensor comprising a pixel matrix having two or more pixel arrays as separate segments logically divided in the pixel matrix. Such a method comprises steps of: detecting a presence of an object having a biometric pattern on the sensor, performing a coarse scan (a pre-scan) by scanning a fraction of pixels in a pixel array to determine a contact boundary between the object and the sensor, and performing a detailed scan selectively within the contact boundary to provide the image data of the biometric pattern. 
     In some embodiments, the sensor is a fingerprint sensor, the object includes at least one finger, and the biometric pattern is a fingerprint. 
     As described herein, each pixel array comprises a plurality of pixels arranged in a plurality of rows and a plurality of columns. The plurality of pixels comprise thermal sensing pixels. Each pixel array may further comprise a capacitive sensing grid having capacitive sensing nodes distributed in each pixel array. 
     In such a method, the presence of an object such as a finger touch on the sensor is detected through the thermal sensing pixels or the capacitive sensing nodes. The coarse scan and the detailed scan are performed through the thermal sensing pixels. 
     Such a method may further comprise dynamically tracking rolling motion and location of the object through a capacitive scan using the capacitive sensing nodes. The method may further comprise a step or steps for combining biometric images of the object captured through thermal scans during the rolling motion of the object to provide a complete biometric pattern using the MCU. 
     In some embodiments, the capacitive sensing nodes are mutual capacitance sensing nodes or self-capacitance sensing nodes. The self-capacitance sensing nodes may be passive-matrix addressed, or active-matrix addressed by an array of thin film transistors. The mutual capacitance sensing nodes are configured to be passive-matrix addressed. 
     The sensor, the device, the system, and the method provided in the present disclosure provide significant benefits, which the existing technologies cannot provide. For example, the technology provided in the present disclosure provide faster scan time, lower total power consumption, improved image scan bandwidth, capability of scanning a moving/rolling object (such as a finger or multiple fingers), and high resolution. For example, a large fingerprint sensor or system can be provided to meet fingerprint acquisition profile (FAP) standards. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The present disclosure is best understood from the following detailed description when read in conjunction with the accompanying drawings. It is emphasized that, according to common practice, the various features of the drawings are not necessarily to scale. On the contrary, the dimensions of the various features are arbitrarily expanded or reduced for clarity. Like reference numerals denote like features throughout specification and drawings. 
         FIG. 1  is a block diagram illustrating an exemplary system such as biometric sensor system in accordance with some embodiments. 
         FIG. 2  shows a schematic illustration of an exemplary sensor or device such as a fingerprint sensor or device in accordance with some embodiments. 
         FIG. 3  illustrates different contact areas of a rolling finger on a fingerprint sensor. 
         FIG. 4A  illustrates a pixel array in some embodiments. 
         FIGS. 4B-4C  illustrates two exemplary pixel matrices with multi-segment sensing areas and pixel arrays in accordance with some embodiments. 
         FIG. 5A  illustrates a device such as a fingerprint sensor having the pixel array of  FIG. 4A  in some embodiments. 
         FIG. 5B  illustrates an exemplary device such as a finger sensor having a multi-segment pixel matrix (e.g., that of  FIG. 4C  for illustration) in accordance with some embodiments. 
         FIG. 6  illustrates an exemplary device such as a finger sensor having a multi-segment pixel matrix (e.g., that of  FIG. 4C  for illustration) with switches in accordance with some embodiments. 
         FIG. 7  is a flow chart illustrating a method of selective active thermal scan using an exemplary device such as a finger sensor having a multi-segment pixel matrix (or called multiple pixel arrays) in accordance with some embodiments. 
         FIGS. 8A-8C  illustrate the fingerprints from three steps of the method of  FIG. 7 , including finger detection ( FIG. 8A ), fast pre-scan ( FIG. 8B ), and detailed fingerprint scan ( FIG. 8C ), in accordance with some embodiments. 
         FIG. 9  illustrates an exemplary sensor such as a finger sensor having both a multi-segment pixel matrix and a 2-D capacitive sensing grid having capacitive sensing nodes in accordance with some embodiments. 
         FIG. 10  shows two examples of rectangular fingerprint scan boundary for a finger in an unrotated state (A) and a rotated state. 
         FIGS. 11A-11C  illustrate three examples of fingerprint scan boundary in the three steps of the method of  FIG. 7 , including finger detection ( FIG. 11A ), fast pre-scan ( FIG. 11B ), and detailed fingerprint scan ( FIG. 11C ), in accordance with some embodiments. 
         FIG. 12  illustrates a process of finger rolling scan operation using the exemplary system in accordance with some embodiments. 
         FIG. 13  illustrates a process of continuously capturing images of a rolling finger using the exemplary system in accordance with some embodiments. 
         FIG. 14  illustrates a process of capturing images of a rolling finger with minimal image capture times using the exemplary system so as to reducing the total image scan power consumption in accordance with some embodiments. 
         FIG. 15  is a flow chart illustrating an exemplary method for biometric sensing in accordance with some embodiments. 
     
    
    
     DETAILED DESCRIPTION 
     This description of the exemplary embodiments is intended to be read in connection with the accompanying drawings, which are to be considered part of the entire written description. In the description, relative terms such as “lower,” “upper,” “horizontal,” “vertical,”, “above,” “below,” “up,” “down,” “top” and “bottom” as well as derivative thereof (e.g., “horizontally,” “downwardly,” “upwardly,” etc.) should be construed to refer to the orientation as then described or as shown in the drawing under discussion. These relative terms are for convenience of description and do not require that the apparatus be constructed or operated in a particular orientation. Terms concerning attachments, coupling and the like, such as “connected” and “interconnected,” refer to a relationship wherein structures are secured or attached to one another either directly or indirectly through intervening structures, as well as both movable or rigid attachments or relationships, unless expressly described otherwise. 
     For purposes of the description hereinafter, it is to be understood that the embodiments described below may assume alternative variations and embodiments. It is also to be understood that the specific articles, compositions, and/or processes described herein are exemplary and should not be considered as limiting. 
     In the present disclosure the singular forms “a,” “an,” and “the” include the plural reference, and reference to a particular numerical value includes at least that particular value, unless the context clearly indicates otherwise. When values are expressed as approximations, by use of the antecedent “about,” it will be understood that the particular value forms another embodiment. As used herein, “about X” (where X is a numerical value) preferably refers to ±10% of the recited value, inclusive. For example, the phrase “about 8” preferably refers to a value of 7.2 to 8.8, inclusive. Where present, all ranges are inclusive and combinable. For example, when a range of “1 to 5” is recited, the recited range should be construed as including ranges “1 to 4”, “1 to 3”, “1-2”, “1-2 &amp; 4-5”, “1-3 &amp; 5”, “2-5”, and the like. In addition, when a list of alternatives is positively provided, such listing can be interpreted to mean that any of the alternatives may be excluded, e.g., by a negative limitation in the claims. For example, when a range of “1 to 5” is recited, the recited range may be construed as including situations whereby any of 1, 2, 3, 4, or 5 are negatively excluded; thus, a recitation of “1 to 5” may be construed as “1 and 3-5, but not 2”, or simply “wherein 2 is not included.” It is intended that any component, element, attribute, or step that is positively recited herein may be explicitly excluded in the claims, whether such components, elements, attributes, or steps are listed as alternatives or whether they are recited in isolation. 
     Unless expressly indicated otherwise, the term “connected” or “coupled” used herein are understood to encompass different connections or coupling between or among the components so as to conduct electricity or transmit signals for communication. Such a connection or coupling can be through wire, wireless, or cloud-based modes. 
     The present disclosure provides a multi-segment pixel matrix, a sensor or device, an apparatus, a system, and a method, for sensing such as biometric sensing. The present disclosure also provides a method of making the multi-segment pixel matrix, the sensor, the device, an apparatus, and a system. The present disclosure is described using finger as an exemplary object and fingerprint as an example of biometric pattern, for the purpose of illustration only. The products and the method provided in the present disclosure can be used for measuring patterns in a partially heat conducting surface of an object in general. For example, such an object can be a hand palm or a skin in other parts of a human body. 
     Large fingerprint sensing area has been highly desirable because it captures more fingerprint information in a single scan providing higher identification accuracy with lower false acceptance and false rejection rate. At the same time, a high fingerprint scan resolution is necessary to obtain a high-quality fingerprint image precisely capturing the fingerprint minutiae, ridge contours and edge features. Such detail is crucial for a high confidence fingerprint matching and enables anti-spoofing capability to differentiate between real and fake fingers. The FBI certified Personal Identity Verification (PIV) and Image Quality Standard (IQS) require a minimum sensor resolution of 500 dpi. Both large sensing area and high scan resolution requirements imply that the sensing system must have sufficiently high bandwidth to collect complete fingerprint image from a large number of pixels on the sensor within a reasonable scan time. 
     Large fingerprint sensor capable of simultaneously scanning multiple fingers are gaining popularity in consumer electronics and is becoming increasingly essential for law enforcement agencies, border patrol, and other high security applications. In particular, FAP60 fingerprint sensor, which can simultaneously scan four fingers and capture a continuous fingerprint from a rolling finger is the de-facto standard for government offices, custom immigration, and military applications. Therefore, to meet the increasing demands, the next generation fingerprint sensor must have extremely high image scan and processing bandwidth capable of collecting high resolution fingerprint image from an ultra large sensing area, identifying multiple individual fingerprints, as well as dynamically collecting fingerprint from a moving finger rolling across the sensor. 
     The active thermal principle is one of the preferred solutions for implementing ultra large and high-resolution fingerprint acquisition profile (FAP) standard fingerprint sensors. It is inherently immune to sunlight interference and works well with wet or sweaty fingers. It offers a thin form factor, lightweight and cost-effective alternative to the optical counterparts. These features are highly desirable for integrating into mobile applications and for wider adoption in civilian applications. This technology provided in the present disclosure significantly improves the scan bandwidth, scan time and energy consumption by adopting a new sensing system architecture enabling the next generation active thermal sensor to be competitive against the optical sensors. 
     The present disclosure is described with selective active thermal sensing as the main scan method. The technology such as multi-segment architecture as described herein may be also used for the sensor and the system with the optical scan as the main scan method. 
     In  FIGS. 1-14 , like items are indicated by like reference numerals, and for brevity, descriptions of the structure, provided above with reference to the preceding figures, are not repeated. The methods described in  FIGS. 7-8 and 11-15  are described with reference to the exemplary structure described in  FIGS. 1-6 and 9 . 
       FIG. 1  is a schematic diagram of an exemplary system such as a biometric sensor system  100  in accordance with some embodiments. Such an exemplary system can be one possible architecture for a biometric system. 
     Referring to  FIG. 1 , in the illustrated embodiment, the biometric sensor 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  is in communication with the biometric sensor  10  through interface  11 , and the MCU  60  is in communication with the ASIC  50  through interface  51 . Either or both of the ASIC  50  and the MCU  60  may be embedded in one chip. The biometric sensor  10  is configured, under control of the ASIC  50 , to capture an image of a biometric pattern such as a fingerprint and transmit image data as signals through the interface  11 . In some embodiments, the biometric sensor  10  outputs analog signals, and interface  11  is an analog interface. The ASIC  50  can receive the analog signals and perform an analog-to-digital conversion (“A/D conversion”) before sending the image data to the MCU  60 . 
     Alternatively, in some embodiments, the A/D conversion can occur within fingerprint sensor  10  such that biometric sensor  10  outputs a digital signal and interface  11  is a digital interface. For example, in embodiments in which the biometric sensor  10  includes a matrix of pixels (as described below), each pixel may include A/D conversion and output a digital signal to the ASIC  50 . In some embodiments, the fingerprint sensor  10  can 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 MCU  60  can evaluate those signals to determine a presence and location of a specimen on the biometric sensor  10 . That information is used by the ASIC  50  and/or MCU  60  to control scanning. For example, the ASIC  50  and/or MCU  60  can identify a sub-portion of the biometric sensor  10 , and the ASIC  50  can direct the biometric sensor  10  to scan only the sub-portion. 
     The ASIC  50 , which can be a processing chip, reads the image data from the biometric sensor  10  and transfers it to the MCU  60  via the interface  51  (e.g., SPI, USB, or other suitable interface). The MCU  60  processes the image data, extracts characteristic features, and generates a fingerprint template (e.g., an image of the fingerprint), for example, based on so-called “minutiae” in the image data. In some embodiments, the MCU  60  is provided with a fingerprint matching functionality that compares the fingerprint template to one or more stored fingerprints (e.g., corresponding to the fingerprints of authorized persons) to determine whether the template matches any of the stored fingerprints. In some embodiments, the ASIC  50  and the MCU  60  are components of an image acquisition controller  70 . In various embodiments, the image acquisition controller  70  also includes one or more processors (not shown), which may be part of a host system (e.g., a smartphone, smart card, etc.) into which the biometric sensor system  100  is integrated. 
     In various embodiments, the functionality of ASIC  50 , MCU  60 , the image acquisition controller  70 , and/or a smart card chip (not shown) can be integrated into a single chip or chips within the host system. For example, the biometric sensor system  100  may 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 appropriate application. In some embodiments, such as for smart credit card embodiments, the fingerprint template may be transferred to a smart card chip (integrated circuit card chip, ICC) where the storage and matching is performed in a so-called on-card biometric comparison application, sometimes also called “match on card” or “match on SE” (secure element). 
     In accordance with some embodiments, the MCU  60  itself can be the controller for the system  100 , and is configured to control the operation of the whole fingerprint module or system  100 . For example, the functions of the MCU  60  may range from detecting finger presence, collecting or scanning for fingerprint, to processing the image and encrypting the image to a host. Sometimes the functions of the MCU  60  may depend on how much a user wants to be done in the MCU  60 . In some embodiments where “match on chip” is required, the MCU  60  compares the collected fingerprint and determine if it matches the one previously stored in the MCU  60 . In some embodiments, the user may want the MCU  60  just to provide a complete image and the image will be “matched” in the host system (e.g., MSFT Windows Hello). However, in some other applications, a user may want to have more control over the module operation and the MCU  60  is configured to perform in respond to the specific commands from the host. 
     Referring to  FIGS. 1 and 2 , in some embodiments, both the fingerprint sensor  10  and the ASIC  50  may be disposed on one substrate, and are referred as a fingerprint sensor or a fingerprint sensing device  15 .  FIG. 2  is a partially schematic illustration of an exemplary biometrics (e.g., fingerprint) sensor or biometric (e.g., fingerprint) sensing device  15  in an exemplary system in accordance with some embodiments. The MCU  60  may be disposed in the biometric sensing device  15 , or separate from while connected with the biometric sensing device  15 . 
     Referring to  FIG. 2 , in the illustrated embodiment, the biometric sensing device  15  comprises a biometric sensor  10 , which comprises a substrate  14 , a pixel matrix  16  for the biometric sensor  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, the ASIC  50  can be mounted to the substrate  14 , for example, as shown in  FIG. 2 . In some embodiments, the biometric sensor  10  is a flexible sensor and substrate  14  is a flexible material. In various embodiments, the substrate  14  can also be constructed from a polymer, a metal foil, a semiconductor material, quartz, glass, or any other materials or a combination thereof, which is suitable for depositing microelectronic structures in production. Examples of a suitable polymer material include, but are not limited to, polyethylene terephthalate (PET), polyethylene naphthalate, and polyimide. Examples of a suitable metal foil include, but are not limited to, steel, aluminum, and a metal alloy. Examples of a suitable semiconductor material include, but are not limited to, silicon and an III-V semiconductor material. In some embodiments, the substrate  14  is made of a flexible material such as polyimide and a metal foil. 
     As illustrated in  FIG. 2 , the pixel matrix  16  is positioned over a surface of the substrate  14 . In some embodiments, the pixel matrix  16  is formed over 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. The connection points  53  are electrically coupled to the pixel matrix  16 , for example, communicatively via the ASIC  50 , and allow for connection to an external system, for example, the MCU  60  ( FIG. 1 ). In some embodiments, a protective coating (not illustrated) may be applied over pixel matrix  16 . As will be described further herein, the surrounding circuitry  52  includes address lines that allow certain rows or columns of pixel matrix  16 , or rows or column in a certain area of the pixel matrix  16 , to be selectively scanned or read. 
     In various embodiments, the biometric sensor  10  operates on the active thermal sensing principle. In such embodiments, a low power heat pulse is applied to each sensor pixel over a short period of time and a response is measured. This type of fingerprint sensor can be produced through large area production processes, such as those that form LTPS thin film transistors and devices. Based on the active thermal principle, active thermal sensors measure the heat conductance of an object for a given heating stimulus. Examples of the active thermal sensing principle suitable for the biometric sensor  10  in the present disclosure are disclosed in U.S. Pat. No. 6,091,837 to Dinh, entitled “Sensor for Acquiring a Fingerprint Image Based on Heat Transfer” and U.S. Pat. No. 8,724,860, also to Dinh, entitled “Apparatus for Fingerprint Sensing and Other Measurements,” the entireties of each of which are incorporated by reference herein. The response to the stimulus is measured by each of the sensing sites within a sensor array. The thermal response of an element is in part a function of the stimulus provided, i.e., the larger the stimulus, the larger the response. Sensing sites are heated by application of an electrical current to the site. 
     The thermal sensor principle utilizes heat transfer mechanism in order to distinguish fingerprint valleys and ridges, as their skin structures have different heat transfer characteristics. A short heat pulse is applied to selected pixels in a sensor array (or a portion of a sensor array as described herein), and the heat exchange between the finger and the underlying individual sensors is monitored through a sensor temperature variation measurement. A relatively high sensor temperature indicates a little heat loss or a small heat exchange between the considered sensor and the finger at this point because of low thermal conductivity. The points with low thermal conductivity map the local fingerprint valley structure, and the points with high thermal conductivity, i.e., having high heat conduction/transfer, map the local fingerprint ridges structure. Intermediate thermal conductivity points correspond to the local transition zone between ridges and valleys. The 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. 
     Each pixel array described herein comprises sensor element or pixel  18  such as thermal sensing pixels  19  (as illustrated in  FIG. 2 ). A pixel array may be a two-dimensional network of pixels  18 . In some embodiments, a pixel or sensor element may include one or more diodes connected in series between a pixel row line and a pixel column line. The diodes are close to the sensor surface and in good thermal contact with a fingerprint to be measured, and may act as both pixel heater and temperature sensing element. 
     The pixel heating power is proportional to the product of the number of the diodes, a given current and voltage across each diode. The diodes are temperature sensitive, and any temperature change in a pixel reflects a corresponding change in voltage if the current is biased, or reflects a corresponding change in current if the voltage is biased. 
     The pixel diodes can be any microelectronic device construction, with either purely or combined rectifying characteristic. Examples of a suitable diode include, but are not limited to a PN-junction rectifier, a Schottky rectifier, a PIN diode, or any combination thereof. The diodes may be constructed from a compound-semiconductor such as germanium or silicon, or metal such as aluminum with suitable properties, or from organic materials. The atomic structures may be mono-crystalline, amorphous or poly-crystalline. 
     The pixels may be covered with a conductive or semiconductor layer (not shown), which can be grounded to shield and protect the sensor. A protective coating (not shown) may be coated on the conductive or semiconductor layer to provide mechanical and chemical protection during uses. 
     Table 1 summarizes the fingerprint acquisition profile (FAP) standard sensor specifications, which are defined in the FBI specification PIV-071006 and Electronic Biometric Transmission Specifications (EBTS) Appendix F. The total number of pixels of FAP60 sensor is 20 times more than FAP20 sensor. Therefore, the FAP60 sensing bandwidth and throughput must be proportionally scaled up to stay within a reasonable scan time. 
     
       
         
           
               
               
               
               
               
               
               
             
               
                   
                 TABLE 1 
               
               
                   
                   
               
               
                   
                 FAP20 
                 FAP30 
                 FAP40/45 
                 FAP50 
                 FAP60 
                 Unit 
               
               
                   
                   
               
             
            
               
                   
               
            
           
           
               
               
               
               
               
               
               
            
               
                 Pixels 
                 400 × 300 
                 500 × 400 
                 800 × 750 
                 1600 × 1000 
                 1600 × 1500 
                 — 
               
               
                   
                 120k 
                 200k 
                 600k 
                 1600k 
                 2400k 
                 pixels 
               
            
           
           
               
               
               
            
               
                 Resolution 
                 500 
                 dpi 
               
            
           
           
               
               
               
               
               
               
               
            
               
                 Dimensions 
                 0.8 × 0.6 
                 1.0 × 0.8 
                 1.6 × 1.5 
                 3.2 × 2.0 
                 3.2 × 3.0 
                 inch 
               
               
                   
                 20.3 × 15.2 
                 25.4 × 20.3 
                 40.6 × 38.1 
                 81.3 × 50.8 
                 81.3 × 76.2 
                 mm 
               
               
                 Active 
                 309.7 
                 516.1 
                 1548.4 
                 4129.0 
                 6193.5 
                 mm 2   
               
               
                 Area 
                 1 
                 1.67 
                 5.0 
                 13.3 
                 20.0 
                 (normalized) 
               
               
                 Number of 
                 1 
                 1 
                 2 
                 4 
                 4 
                 — 
               
               
                 Fingerprint 
               
               
                   
               
            
           
         
       
     
     Another challenge for the next generation fingerprint sensor is to capture a continuous fingerprint from a rolling finger as illustrated in  FIG. 3 . As illustrated in  FIG. 3 , from position (A), to (B), to (C), to (D), and then to (E), a finger  70  having a finger nail  71  is rolled from one side to the other side on a sensor  10 . The finger nail  71  is on one side (i.e., top side) of the finger  70 , while the fingerprint is on the opposite of the finger  70 . In the position (C), the finger  70  is pressed onto the sensor  10  and has the largest contacting area. Unlike stationary finger, only a portion of the full fingerprint is in contact with the sensor  10  available for image capture at any given moment. Each partial fingerprint of a rolling finger will only briefly contact the sensing surface leaving a short time window to properly capture the moving fingerprint. This requires not only a high bandwidth sensing system, but also an intelligent sensing system to accurately locate and track the finger movement allocating the available scan resources to generate a high-quality fingerprint image. 
     This present disclosure enables and provides large area fingerprint sensors meeting various FAP specifications up to FAP60 based on active thermal sensing principle by expanding the sensing bandwidth. 
     In accordance with some embodiments, an exemplary system  100  for biometric sensing comprises a sensor  10 , which comprises a pixel matrix  16  having two or more pixel arrays (e.g.,  36 A,  36 B,  36 C and  36 D in  FIGS. 4B-4C, 5B and 6 ) as separate segments logically divided in the pixel matrix  16 . A pixel matrix is logically divided into multiple segments. 
     The terms “logical division” or “logically divided” used herein refer to that a pixel array (i.e., a full pixel array) is re-arranged or sub-divided into multiple segments (multiple pixel arrays) to facility the image collection or image sensing. No visual boundary or physical gaps exist between the sub-divisions that a user will notice. “Logical division” in electrical engineering in general refers to logically sub-divide a larger task into several smaller tasks to improve performance, while all the tasks may be treated or processed in the same way consistently and uniformly. 
     Referring to  FIG. 4A , the pixel matrix  16  includes one single pixel array  26 . 
     Referring to  FIGS. 4B and 4C , two exemplary pixel matrices  16  have multi-segment image sensing and processing architecture are shown. As illustrated in  FIGS. 4B-4C , each pixel matrix  16  has multiple pixel arrays  36  logically divided in the pixel matrix  16 . In  FIG. 4B , two pixel arrays  36  (A, B) are shown. In  FIG. 4C , four pixel arrays  36  (A, B, C, D) are shown. Such a new sensor architecture is designed and configured that the large sensing area can 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 dimensions and image resolution, and there is no physical gap between the adjacent segments. This partition allows the active sensing area to be scanned in parallel by multiple ASICs  50 . 
     In some embodiments, the pixel matrix comprises any suitable number of pixel arrays, for example, from 2 to about 12 pixel arrays, from 2 to 8 pixel arrays, from 2 to 6 pixel arrays, from 2 to 4 pixel arrays. The number of the pixel arrays (or segments) can be any integer in a range of from 2 to 12. For example, the number of pixel arrays or segments may 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 physical implementation in the device fabrication. For example, for some IC or TFT processes with only 2 to 3 metal layers, the number of pixel array may be low, for example, about 2-4 pixel arrays. For another example, for a process with 6 or more metal routing layers, more pixel arrays such as 8 or more than 8 arrays can be readily supported. 
     As described in  FIG. 2 , in some embodiments, each pixel array  36  comprises a plurality of pixels arranged in a plurality of rows and a plurality of columns. Each pixel array may have a respective invisible boundary. Each pixel array  36  comprises thermal sensing pixels, which are configured to operate based on the active thermal sensing principle, in which a power heat pulse is applied to each pixel array and a response corresponding to a biometric pattern is measured. For thermal sensing, a pixel in each pixel array may comprise one or more diodes connected in series between a pixel row line and a pixel column line. 
     Referring to  FIGS. 5A-5B , as also described in  FIGS. 1-2 , the sensor or the sensing device  15  includes at least one application-specific intergrade circuits (ASIC)  50  and at least supporting circuits  52 . 
       FIG. 5A  shows an exemplary device  15  including a single pixel array  26 .  FIG. 5B  illustrates an exemplary sensor or device  15  comprising multiple pixel arrays  36 . As shown in  FIG. 5B , the sensor or device  15  may further comprise a plurality of ASICs  50  (labeled as  50 A,  50 B,  50 C, and  50 D) and a plurality of supporting circuits  52  (labeled as  52 A,  52 B, . . .  52 H). Each pixel array  36  is connected with at least one supporting 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 independently driven and scanned by one or more of the plurality of the ASICs  50 . In  FIG. 5B , “Ckt” means “circuit.” Sometimes, one ASIC  50  may be directed to scan image across multiple pixel arrays  36 . On the other hand, one pixel array  36  can be driven by multiple ASICs  50 . There might be multiple such as four different types of supporting circuits around a pixel array for delivering the input signal to the corresponding pixels during scan and for collecting the corresponding analog data to an ASIC  50  to generate a fingerprint image. The circuits are similar to the decoder circuit and readout circuit for SRAM or any memory product. 
     In some embodiments, each pixel array or segment  36  is driven and scanned by an individual ASIC ( FIG. 5B ). If the active sensing area is logically divided into 4 segments, 4 ASICs  50  are configured to work in parallel. Image scan bandwidth is increased by 4 times, and it takes about a quarter of the original scan time to collect a full image. In other words, the scan time to collect a full image is reduced to 1/N of the original scan time, where N is the number of divided segments. 
     Referring to  FIG. 6 , in some embodiments, the sensor or device  15  in the system  100  may further comprise a plurality of switches  54  (e.g., labeled as  54 A,  54 B,  54 C, and  54 D). The label “SW” in  FIG. 6  means a switch. Each switch  54  is connected with one or more supporting 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 the ASICs  50  through one or more switches  54 . In some embodiments, such a switch  54  is an electronic contact switch. The signal from the thermal sensing elements in a pixel array may be addressed and controlled using an electronic contact switch, e.g. a double gate MosFET transistor. 
     In some embodiments, the plurality of ASICs  50  and the sensor  10  are disposed together within a biometric sensing device  15 . The sensor or device  15  illustrated in  FIGS. 5B and 6  is a part of the system  100 . As described in  FIG. 1 , the system  100  may further comprise a microcontroller unit (MCU)  60  coupled to the plurality of ASICs  50 . The MCU  60  comprises one or more processor and at least one tangible, non-transitory machine readable medium encoded with one or more programs configured to process the image data and/or control operation of the system. In some embodiments, the number of ASICs may correspond to the number of the pixel arrays. The system  100  may include only one MCU  60 . 
     With a switch  54 , a user can choose to one ASIC  50  dedicated for each pixel array  36 , or having multiple ASICs  50  processing one pixel array  36  to improve scanning speed and bandwidth. One powerful MCU  60  can be used to manage all the ASICs  50  and the MCU  60  can decide how to best arrange resources to minimize scan time, to improve scan quality, or both. 
     Referring to  FIG. 6 , in some embodiments, each pixel array segment  36  can be independently driven and simultaneously scanned by multiple ASICs  50 . In the arrangement shown in  FIG. 6 , multiple ASICs  50  can operate together to collect fingerprint image from the same pixel array segment  36  at the same time. This arrangement is particularly useful to collect fingerprint image from one or more specific pixel array segments  36 . Scan resources are redirected to work in parallel accelerating fingerprint scan for specific local areas. 
     The FAP60 sensing area (81.3×76.2 mm) is much larger compared to the fingerprint size. Even for the 4-finger scan, fingerprints only occupy a small portion of the total sensing area. In most situations, fingerprints cover less than 15% of the total sensing area. 
     In another aspect, at least two steps of a selective thermal scan can be used in accordance with some embodiments. A coarse low-resolution thermal scan is used to detect and locate fingerprints so that the high-resolution thermal scan is performed to capture image only at the sensing areas where fingerprints are located. Instead of collecting a full image from the whole sensing area, sensing system intelligently selects the areas of interest for the detail fingerprint thermal scan, significantly decreasing thermal scan activities. Therefore, scan time and scan energy consumption are proportionally reduced. 
     A scan resolution is high when it is 500 dpi or above. 500 dpi is the FBI FAP sensor standard for fingerprint image collection. Low scan resolution may be 100 dpi or lower, for example. The objective is mainly to locate where a finger is at or where the fingerprint boundary is so that no time or effort is wasted on scanning areas without value. 
     Through the MCU  60 , the system  100  is configured to perform the functions and steps as described herein. Referring to  FIG. 7 , for example, an exemplary method  200  comprises at least three steps. A first step is to detect a presence of an object having a biometric pattern on the sensor. A second step is to perform a coarse scan by scanning a fraction of pixels in a pixel array to determine a contact boundary between the object and the sensor. A third step is to perform a detailed scan selectively within the contact boundary to provide the image data of the biometric pattern. 
     Referring to  FIG. 7 , during a standby mode, as shown in block  110 , the sensing system  100  periodically executes an initial thermal scan (or by capacitive scan using capacitive sensing grid described below in  FIG. 9 ) at a low resolution to detect the presence of finger touch(es) on the sensor. Only a small percentage of pixels (for example, 2%) evenly spread across the sensor pixel array are selected for the finger detection. Once finger touches are detected and are found to be in stable contact with the sensor (block  112 ), the system  100  enters the next pre-scan (a coarse thermal scan) stage selecting another set of pixels around the identified finger touch areas to determine fingerprint boundaries (block  114 ). The system  100  could select a higher percentage of pixels (for example, 8%) around the identified touch areas to improve boundary computation precision. Afterward, as shown in block  116 , a thermal scan with full resolution (i.e., a detailed thermal) is performed to collect detail fingerprint image within the identified boundaries. The fingerprint scan area is only a small subset of the full pixel array. 
     Referring to  FIG. 8 , examples of the steps in  FIG. 7  are further illustrated, including finger detection ( FIG. 8A ), fast pre-scan ( FIG. 8B ), and detailed fingerprint scan ( FIG. 8C ). The fingerprint  72  and the touch area  74  and the scan area  76  are shown in  FIGS. 8A-8C . 
     By using the method  200 , the selective scanning method not only greatly improves image scanning and energy consumption, but also considerably reduces subsequent image processing computational efforts and the memory requirement. 
     By combining both the multi-segment sensing and the selective thermal scan, image sensing bandwidth and throughput are more than one order of magnitude higher than those in the conventional technology. This will significantly close the scan time performance gap enabling a fingerprint sensor to meet the FAP60 sensor requirements, while the low image scan power consumption makes it favorable over the existing counterparts such as existing optical technology. 
     The steps in the method  200  may also include those for detecting rolling motion and location, combining images, and processing and comparing image data as described in the present disclosure. 
     In another aspect, the large fingerprint sensor can be further enhanced for mobile applications by integrating capacitive scan to achieve an ultra-low standby mode power consumption. Using coarse thermal scan for finger detection often runs into a tradeoff between power consumption and detection response; it is desirable to detect finger presence more frequently to improve system response, but standby power will increase proportionally. Capacitive scan runs considerably faster and consumes lower power than thermal scan. Integrating capacitive scan allows sensing system to detect finger touch more often while maintaining a very low standby power consumption. In addition, the projected capacitance field generated by each capacitive sensing node covers a much wider area and a larger three-dimensional (3-D) space than a thermal scan pixel. A proper placement of capacitive sensing nodes can provide a continuous and broader detection coverage across the entire pixel array. In addition to more frequent detection, capacitive scan improves finger detection accuracy and resolution, a potentially more effective solution at a lower operating cost. 
     Referring to  FIG. 9 , in accordance with some embodiments, an exemplary sensor  10  further comprises a capacitive sensing grid  78 , which comprising capacitive sensing nodes  78   a  (illustrated as dots in  FIG. 9 ) distributed in each pixel array  36  or in the pixel matrix  16 . The lines in  FIG. 9  represent the pixel array  36  for thermal scans. The system or device may further comprise an auxiliary circuit (not shown) for the capacitive sensing grid  78  in a respective ASIC or in the MCU. The auxiliary circuit can be also an independent IC outside the respective ASIC or the MCU. The capacitive sensing grid  78  is connected with the auxiliary circuit. To enable a capacitive scan, a 2-D grid of capacitive sensing nodes  78   a  across the active sensing area is integrated into the fingerprint sensor  10  as illustrated in  FIG. 9 . The grid  78  of capacitive sensing nodes  78   a  is coarser than the pixel array  36  having thermal sensing pixels  19 . The grid  78  can be implemented in each pixel array  36  or implemented in the pixel matrix  16 . 
     Because of the improved detection accuracy and resolution, the fast capacitive scan can be used not only to identify the presence of finger(s) on sensor during standby mode, but also to locate the position and estimate the size of each finger touch more precisely. Once fingers are in stable contact with the sensor, system runs a similar coarse thermal scan (fast Pre-Scan) to confirm finger presence and to compute the proper fingerprint boundaries. 
     In some embodiments, the 2-D grid of capacitive sensing nodes can be implemented using mutual capacitive sensing with X number of transmitting electrodes (Tx) and Y number of receiving electrodes (Rx). Passive-matrix addressed mutual capacitive scan supports multi-touch capability and is relatively low cost. The Tx and Rx electrodes can be embedded into the fingerprint sensor and evenly spaced across the pixel array. In one example, Tx electrodes are evenly spaced across the long side of the pixel array with K number of pixels in between 2 adjacent electrodes. Rx electrodes are evenly spaced across the short side of the pixel array with M number of pixels in between 2 adjacent electrodes. K and M are adjustable numbers based on the product resolution and other performance specifications. In another example, Tx electrodes are evenly spaced across the short side of the pixel array and Rx electrodes are evenly spaced across the long side of the pixel array. 
     In another embodiment, the 2-D grid  78  of capacitive sensing nodes are implemented using active-matrix addressed self-capacitive sensing. Self-capacitive sensing can offer higher sensitivity and higher touch resolution than mutual-capacitive sensing at a cost of more signal routings and implementation overhead to address the self-capacitive sensing nodes. 
     The selective thermal scan not only notably reduces fingerprint scan area, but also empowers the sensing system to be able to determine a custom fingerprint boundary specifically for each finger optimizing scan coverage and further minimizing unnecessary scan activities. With a large sensor like FAP60, fingerprints could come in at any angle as long as they are within the sensing area. Fingerprints could be rotated on the sensing area, or each finger could be orientated differently. 
     As illustrated in  FIG. 10 , the two fingerprints are identical with the one on the right rotated by 45°. To cover the complete fingerprint, rectangular scan boundary for the rotated fingerprint requires scanning roughly 25% larger area as compared to the unrotated one, more empty pixels are scanned proportionally driving up scan time and energy consumption. 
     The accuracy of finger touch location and size estimate is much improved with the use of capacitive scan. The fast Pre-Scan therefore can better rely on the finger information collected from capacitive scan and strategically select a small amount of thermal sensing pixels around the projected fingerprint perimeter to compute a more precise and customized fingerprint outline for the subsequent detail fingerprint thermal scan. Instead of using a fixed size or a rectangular boundary  76 , scan boundary  74  can be irregular and tailor-made for each detected fingerprint  72  as illustrated in  FIGS. 11A-11C . This further minimizes unnecessary scan activity over the non-contact or unoccupied pixels which helps maintain a more consistent scan time between rotated and unrotated fingers. 
     In another aspect, the present disclosure provides a sensor or device  15  for biometric sensing as described herein. Such a device  15  comprises a sensor  10  comprising a pixel matrix  16  having two or more pixel arrays  36  as separate segments logically divided in 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 the 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 . 
     In some embodiments, each pixel array  36  comprises a plurality of pixels arranged in a plurality of rows and a plurality of columns, and the plurality of pixels comprise thermal sensing pixels. Each pixel array may further comprise a capacitive sensing grid  78  comprising capacitive sensing nodes  78   a  distributed in each pixel array  36 . The capacitive sensing grid  78  is configured to detect a presence of the object, and/or rolling motion and location of the object. The capacitive sensing nodes  78   a  may be mutual capacitance sensing nodes or self-capacitance sensing nodes. The self-capacitance sensing nodes are configured to be passive-matrix addressed, or active-matrix addressed by an array of thin film transistors. The mutual capacitance sensing nodes are configured to be passive-matrix addressed. 
     The device  15  may further comprise the switches as described herein. The device  15  may also comprise a microcontroller unit (MCU)  60  coupled to the plurality of ASICs  50 . The MCU  60  comprises one or more processor and at least one tangible, non-transitory machine readable medium encoded with one or more programs configured to process the image data and/or control operation of the device as described herein. 
     Table 2 summarizes results of a 4-finger test case study on the experimental examples (FAP 60 sensors) in accordance with some embodiments. The FAP60 active sensing area is logically divided into 8 segments using the multi-segment architecture and each segment is driven and scanned by an individual ASIC. Because the segments are scanned in parallel, full-image scan time is drastically reduced from 13.8 sec to 1.73 sec, eight times faster than the conventional solution. With the selective thermal scan enabled, only fingerprint areas are scanned, and scan time further reduces to 0.67 sec, roughly another 2.5 times faster. The fast pre-scan requires additional time for boundary evaluation and image processing, but this overhead is significantly smaller compared to the time savings from the detail fingerprint image scan. In addition, the total image scan energy consumption is roughly 5 times smaller. Sensor pixel array segments without finger touch are disabled and only the sensor pixels where fingerprints make contact with are activated; this translates to substantially less image scan and processing activities. Further enabling the customer scan boundary feature allows the scan boundaries to more tightly fit around each fingerprint outline bypassing the non-contact pixels, resulting in additional scan time and energy consumption savings. By implementing these innovative features, the test case study shows that scan time is reduced by more than 20 times while energy consumption is reduced by nearly 6 times. 
     
       
         
           
               
               
               
             
               
                 TABLE 2 
               
             
            
               
                   
               
               
                   
                   
                 Energy  
               
               
                   
                 Scan Time 
                 Consumption 
               
            
           
           
               
               
               
               
               
            
               
                   
                 Estimate 
                 Normalized 
                 Estimate 
                 Normalized 
               
               
                   
               
               
                 Conventional  
                 13.8 sec 
                 22.6  
                  577 mJ 
                 5.84 
               
               
                 Architecture  
                   
                   
                   
                   
               
               
                 (single pixel array) 
                   
                   
                   
                   
               
               
                 Multi-Segment  
                 1.73 sec 
                 2.83 
                  577 mJ 
                 5.84 
               
               
                 Architecture  
                   
                   
                   
                   
               
               
                 (8 segments) 
                   
                   
                   
                   
               
               
                 Multi-Segment  
                 0.67 sec 
                 1.10 
                  109 mJ 
                 1.10 
               
               
                 Architecture (8  
                   
                   
                   
                   
               
               
                 segments) +  
                   
                   
                   
                   
               
               
                 Selective Thermal  
                   
                   
                   
                   
               
               
                 Scan (w/ capacitive  
                   
                   
                   
                   
               
               
                 scan) 
                   
                   
                   
                   
               
               
                 Multi-Segment  
                 0.61 sec 
                 1   
                 98.8 mJ 
                 1   
               
               
                 Architecture (8  
                   
                   
                   
                   
               
               
                 segments) +  
                   
                   
                   
                   
               
               
                 Selective Thermal  
                   
                   
                   
                   
               
               
                 Scan (w/ capacitive  
                   
                   
                   
                   
               
               
                 scan) + Custom  
                   
                   
                   
                   
               
               
                 Scan Boundary 
               
               
                   
               
            
           
         
       
     
     As shown in Table 2, compared to the single pixel array, the performance improvement using the multi-segment architecture is significant, including faster scan time and lower total power consumption. The image scan time can be dropped from 13.8 to 0.61 sec (more than 20 times faster), while energy consumption reduces by almost 6 times. These are huge performance improvement. Because of the much improved image scan bandwidth, even a moving/rolling finger can be scanned. This enables a new product feature that we currently cannot support. 
     In addition to improving finger touch evaluation, the interoperation between capacitive scan and thermal scan empowers the sensing system to support finger roll scan for capturing the fingerprint within a short time. The integration of fast capacitive scan enables the sensing system to dynamically track finger movement, determine the proper thermal scan boundaries on the fly, and optimize fingerprint scan operation as finger is rolling across the sensing area for fingerprint capture. In other words, it provides the necessary capabilities to create an intelligent sensing system leveraging the available scan resources to capture a continuous rolling fingerprint. 
       FIG. 12  illustrates an example of operation, in which capacitive sensing nodes  78  are implemented using self-capacitive sensing. The touch value detected by each capacitive sensing node  78  changes as a finger  70  rolling across the sensing area. Touch value increases as a finger approaches, remains constant if it is in full contact, and decreases when the finger rolls away. By continuously monitoring the touch values, sensing system will be able to precisely locate the moving finger  70  at any given moment. Instead of scanning from an arbitrary starting point, the exemplary sensing system  100  can enable the corresponding section of thermal sensing pixels  19  in the pixel array  36  where the rolling finger  70  is currently at as well as to select a smaller subset of pixels currently in contact with the finger  70  to collect detail fingerprint image. In  FIG. 12 , the unscanned thermal pixels  80 , scanned thermal pixels  82  and the actively scanning thermal pixels  84  for a pixel array  36  in the sensor  10  are shown. With this finger tracking capability, thermal scan can be better aligned with the rolling finger in time, location and contact area (scan size) optimizing image scan quality and bandwidth. 
     One technique to improve image quality and signal-to-noise ratio (SNR) is to average multiple images of the same fingerprint area to produce a final image. In some embodiments, because of the higher image scan bandwidth, the sensing system  100  can be configured to continuously capture the rolling finger  70  on the sensor  10  so that the same print area is captured multiple times in consecutive scans as illustrated in  FIG. 13 . The images are then combined together during image processing to create a complete roll fingerprint, and the duplicated sections 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. 
     In some embodiments, the sensing system  100  can be configured to minimize duplicated image captures reducing total image scan power consumption. For example, the sensing system  100  can be set up such that any given fingerprint area is scanned once as illustrated in  FIG. 14 . The total number of scans and scan activities are minimized to save power. For examples, as illustrated in  FIGS. 13-14 , the total number of scans can be decrease from 9 to 5. The optimal total number of scans for each rolling finger may be in a range of 3 to 7. 
     Referring to  FIG. 15 , as described above, an exemplary method  200  for biometric sensing in accordance with some embodiments is generally described. The method  200  is for using a device or a system comprising the exemplary sensor  10  as described. Such a sensor  10  comprises a pixel matrix  16  having two or more pixel arrays  36  as separate segments logically divided in the pixel matrix  16 . Such a method  200  comprises steps  202 ,  204 , ad  206 . 
     At step  202 , a presence of an object having a biometric pattern on the sensor  10  is detected. In some embodiments, the 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  with multiple segments. Each pixel array  36  comprises a plurality of pixels arranged in a plurality of rows and a plurality of columns. The plurality of pixels  18  comprise thermal sensing pixels  19 . Each pixel array  36  may further comprise a capacitive sensing grid  78  having capacitive sensing nodes distributed in each pixel array. 
     At step  204 , a coarse scan (a pre-scan) is performed by scanning a fraction of pixels in a pixel array to determine a contact boundary between the object and the sensor. In such a method, the presence of an object such as a finger  70  touch on the sensor  10  is detected through the thermal sensing pixels  19  or the capacitive sensing nodes  78 . The coarse scan and the detailed scan are performed through the thermal sensing pixels. 
     At step  206 , a detailed scan selectively within the contact boundary is performed to provide the image data of the biometric pattern. 
     At step  208 , as described in  FIGS. 12-14 , rolling motion and location of the object is dynamically tracked through a capacitive scan using the capacitive sensing nodes  78 . In some embodiments, the capacitive sensing nodes  78  are mutual capacitance sensing nodes or self-capacitance sensing nodes. The self-capacitance sensing nodes may be passive-matrix addressed, or active-matrix addressed by an array of thin film transistors. The mutual capacitance sensing nodes are configured to be passive-matrix addressed. 
     At step  210 , biometric images of the object captured through thermal scans during the rolling motion of the object are combined to provide a complete biometric pattern using the MCU. Step  210  may include one or multiple steps. 
     The present disclosure provides at least the products and methods described in the following clauses, which are examples only and do not limit the scope of the disclosure.
     1. A system for biometric sensing, comprising:   

     a sensor comprising a pixel matrix having two or more pixel arrays as separate segments logically divided in the pixel matrix; 
     a plurality of application-specific intergrade 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 the ASICs; and 
     a microcontroller unit (MCU) coupled to the plurality of ASICs and comprising one or more processor and at least one tangible, non-transitory machine readable medium encoded with one or more programs configured to process the image data and/or control operation of the system.
     2. The system of clause 1, wherein the pixel matrix comprises from 2 to about 12 pixel arrays.   3. The system of any of clauses 1-2, wherein the plurality of ASICs and the sensor are disposed together within a biometric sensing device.   4. The system of any of clauses 1-3, wherein the sensor further comprises a plurality of supporting circuits, wherein each pixel array is connected with at least one supporting circuit.   5. The system of any of clauses 1-4, 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 the ASICs through one or more switches.   6. The system of any of clauses 1-5, wherein each pixel array comprises a plurality of pixels arranged in a plurality of rows and a plurality of columns.   7. The system of any of clauses 1-6, wherein each pixel array comprises thermal sensing pixels and is configured to operate based on the active thermal sensing principle, in which a power heat pulse is applied to each pixel array and a response corresponding to a biometric pattern is measured.   8. The system of any of clauses 1-7, wherein a pixel in each pixel array comprises one or more diodes connected in series between a pixel row line and a pixel column line.   9. The system of any of clauses 1-8, wherein each pixel array further comprises a capacitive sensing grid comprising capacitive sensing nodes distributed in each pixel array.   10. The system of clause 9, further comprising an auxiliary circuit in a respective ASIC or in the MCU or outside the respective ASIC or the MCU as an independent integrated circuit, wherein the capacitive sensing grid is connected with the auxiliary circuit.   11. The system of any of clauses 1-9, wherein through the MCU, the system is configured to perform steps comprising:   

     detecting a presence of an object having a biometric pattern on the sensor; 
     performing a coarse scan by scanning a fraction of pixels in a pixel array to determine a contact boundary between the object and the sensor; and 
     performing a detailed scan selectively within the contact boundary to provide the image data of the biometric pattern.
     12. A device for biometric sensing, comprising:   

     a sensor comprising a pixel matrix having two or more pixel arrays as separate segments logically divided in the pixel matrix; and 
     a plurality of application-specific intergrade 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 the 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 of clauses 12-13, wherein each pixel array comprises a plurality of pixels arranged in a plurality of rows and a plurality of columns, and the plurality of pixels comprise thermal sensing pixels.   15. The device of any of clauses 12-14, wherein each pixel array further comprises a capacitive sensing grid comprising capacitive sensing nodes distributed in each pixel array and configured to detect a presence of the object, and/or rolling motion and location of the object.   16. The device of any of clause 15, wherein the capacitive sensing nodes are mutual capacitance sensing nodes or self-capacitance sensing nodes.   17. The device of any of clauses 15-16, wherein the self-capacitance sensing nodes are configured to be passive-matrix addressed, or active-matrix addressed by an array of thin film transistors.   18. The device of any of clauses 15-16, wherein the mutual capacitance sensing nodes are configured to be passive-matrix addressed.   19. The device of any of clauses 12-18, further comprises a microcontroller unit (MCU) coupled to the plurality of ASICs and comprising one or more processor and at least one tangible, non-transitory machine readable medium encoded with one or more programs configured to process the image data and/or control operation of the device.   20. A method of using a device or a system comprising a sensor comprising a pixel matrix having two or more pixel arrays as separate segments logically divided in the pixel matrix, comprising steps of:   

     detecting a presence of an object having a biometric pattern on the sensor; 
     performing a coarse scan by scanning a fraction of pixels in a pixel array to determine a contact boundary between the object and the sensor; and 
     performing a detailed scan selectively within the contact boundary to provide the image data of the biometric 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 of clauses 20-21, wherein each pixel array comprises a plurality of pixels arranged in a plurality of rows and a plurality of columns, the plurality of pixels comprise thermal sensing pixels, and each pixel array further comprises a capacitive sensing grid having capacitive sensing nodes distributed in each pixel array.   23. The method of clause 22, wherein the presence of an object on the sensor is detected through the thermal sensing pixels or the capacitive sensing nodes.   24. The method of any of clauses 22-23, wherein the coarse scan and the detailed scan are performed through the thermal sensing pixels.   25. The method of any of clauses 22-24, further comprising dynamically tracking rolling motion and location of the object through a capacitive scan using the capacitive sensing nodes.   26. The method of any of clauses 21-25, further comprising combining biometric images of the object captured through thermal scans during the rolling motion of the object to provide a complete biometric pattern using the MCU.   27. The method of any of clauses 22-26, wherein the capacitive sensing nodes are mutual capacitance sensing nodes or self-capacitance sensing nodes.   28. The method of any of clauses 22-27, wherein the self-capacitance sensing nodes are passive-matrix addressed, or active-matrix addressed by an array of thin film transistors; and the mutual capacitance sensing nodes are configured to be passive-matrix addressed.   

     The sensor, the device, the system, and the method provided in the present disclosure provide significant benefits, which the existing technologies cannot provide. For example, the technology provided in the present disclosure provide faster scan time, lower total power consumption, improved image scan bandwidth, capability of scanning a moving/rolling object (such as a finger or multiple fingers), and high resolution. For example, a large fingerprint sensor or system can be provided to meet fingerprint acquisition profile (FAP) standards. 
     The methods and system described herein may be at least partially embodied in the form of computer-implemented processes and apparatus for practicing those processes. The disclosed methods may also be at least partially embodied in the form of tangible, non-transient machine readable storage media encoded with computer program code. The media may include, for example, RAMs, ROMs, CD-ROMs, DVD-ROMs, BD-ROMs, hard disk drives, flash memories, or any other non-transient machine-readable storage medium, or any combination of these mediums, wherein, when the computer program code is loaded into and executed by a computer, the computer becomes an apparatus for practicing the method. The methods may also be at least partially embodied in the form of a computer into which computer program code is loaded and/or executed, such that, the computer becomes an apparatus for practicing the methods. When implemented on a general-purpose processor, the computer program code segments configure the processor to create specific logic circuits. The methods may alternatively be at least partially embodied in a digital signal processor formed of application specific integrated circuits for performing the methods. 
     Although the subject matter has been described in terms of exemplary embodiments, it is not limited thereto. Rather, the appended claims should be construed broadly, to include other variants and embodiments, which may be made by those skilled in the art.