TWI778839B - Fingerprint signal processing system and fingerprint signal processing method - Google Patents

Abstract

A fingerprint signal processing system for a fingerprint sensor includes a calibration control circuit, a register circuit, a decode circuit and a normalized circuit. The calibration control circuit is configured to receive a background calibration control signal and an image signal from the fingerprint sensor, and convert the image signal into a plurality of digital signals according to a plurality of offsets. When the background calibration control signal is in a high level, the calibration control circuit is configured to read a plurality of calibration parameters from the register circuit.

Description

Fingerprint signal processing system and fingerprint signal processing method

The present invention relates to a signal processing circuit and a signal processing method. In particular, it relates to a fingerprint signal processing system and a fingerprint signal processing method.

Fingerprint recognition technology has been widely used in various electronic products, such as mobile phones, notebook computers, tablet computers, and portable electronic devices, etc., to realize identity recognition. In the technical framework of the fingerprint sensor, after reading the fingerprint data, it is converted into a digital signal by an analog-to-digital converter (ADC), and there will be a certain offset (offset). In order to correct the offset The conventional method is to correct through the judgment of an algorithm, and this method will slow down the speed of capturing fingerprint data. In view of this, it is necessary to improve the prior art.

One of the objectives of the present invention is to provide a fingerprint signal processing system and a fingerprint signal processing method, which can perform offset correction during encoding, and do not need to be corrected through an algorithm, so that the speed of capturing fingerprint data can be improved. .

One of the objectives of the present invention is to provide a fingerprint signal processing system and a fingerprint signal processing method, which utilizes a target value and a first row formed by the first bit of each row (column) of the encoded image data. Signal, control the background signal to a reasonable value without drifting.

The fingerprint signal processing system and the fingerprint signal processing method of the present invention mainly improve the problem of slowing down the speed of capturing fingerprint data by correcting through the judgment of the algorithm in the past. First, read the calibration parameters stored in the temporary storage circuit through the traces, use the calibration parameters to correct the offset of the analog-digital converter, and then correct the offset generated during decoding by calculating the pixel average value of each row. The shift amount does not need to be corrected by an algorithm, so that the speed of capturing fingerprint data can be improved. Furthermore, the average value of the pixel signal calculated by using the peaks and valleys of the pixel signal is more accurate than the previous algorithm for obtaining the average value and is not easily affected by the fingerprint pressing area.

According to the above, a fingerprint signal processing system for a fingerprint sensor includes: a calibration control circuit which receives a background calibration control signal, receives an encoded analog signal from the fingerprint sensor, and converts the encoded analog signal is a plurality of digital signals, wherein the encoded analog signal is an original image data read by the fingerprint sensor; a temporary storage circuit is electrically connected to the calibration control circuit and stores the digital signals, wherein the digital signals are The signal is stored in a two-dimensional matrix, and a first row of the two-dimensional matrix includes a plurality of calibration parameters, wherein when the background calibration control signal is at a high level, the calibration control circuit reads the A plurality of calibration parameters are used to update a plurality of offsets of the digital signals; and an interpretation circuit is electrically connected to the temporary storage circuit, and the interpretation circuit is used for converting the digital signals into a plurality of pixel signals.

In one example, the fingerprint signal processing system further includes a normalization circuit electrically connected to the decoding circuit, and the normalization circuit normalizes the pixel signals to generate a plurality of normalized pixel signals.

In one example, the calibration control circuit includes: a plurality of analog-to-digital converters for receiving the analog signal, the analog-to-digital converters respectively convert the analog signal into the digital signals according to the corresponding offsets; and an offset The offset correction circuit is electrically connected to the analog-to-digital converter, and the offset correction circuit is used for receiving the background correction control signal, a target parameter (TAR) and the correction parameters, when the background correction control signal is at the high level When , the offsets are updated according to the target parameter or the correction parameters or the above-mentioned combination, so as to generate the corrected offsets.

In one example, when the background correction control signal is at a low level, the offsets are before update or after correction.

In one example, the fingerprint signal processing system further includes a wire electrically connected to the offset correction circuit and the temporary storage circuit.

In one example, the offset correction circuit is used to read the correction parameters stored in the temporary storage circuit from the temporary storage circuit through the wiring, and each of the correction parameters is the data of each row of the original image data. average of.

In one example, an encoded signal of the temporary storage circuit is an N×M matrix, and both N and M are natural numbers. After passing through the decoding circuit, the pixel signals of the N×M matrix are generated, and the N×M Each row of the matrix includes N of the pixel signals, the normalization circuit calculates a pixel average value of the N pixel signals corresponding to each row, and associates the corresponding N pixel signals with the corresponding N pixel signals respectively. The pixel averages are subtracted to generate N normalized pixel signals, and the pixel average is calculated based on less than N of the pixel signals.

In one example, the pixel average value of the row is obtained by calculating the average of an optimal peak pixel signal and an optimal trough pixel signal among the corresponding N pixel signals, and wherein the optimal peak The difference in amplitude between the pixel signal and a base value of the pixel signals in the row is larger than that of the other pixel signals in the row, and the optimal valley pixel signal is different from the base value of the pixel signals in the row. The amplitude difference of the values is smaller than the other pixel signals of the row.

In one example, the pixel average value of the row is obtained by calculating the average of an optimal peak pixel signal and an optimal trough pixel signal among the corresponding N pixel signals; the optimal peak pixel signal The signal at least includes a maximum pixel signal with the largest amplitude difference from a base value of the pixel signals in the row and the average of the pixel signals in other parts; and the optimal valley pixel signal at least includes A minimum value pixel signal with the smallest amplitude difference between a base value of the pixel signals in the row and the average of the pixel signals in other parts.

According to the above, a fingerprint signal processing method for a fingerprint sensor includes: receiving an analog signal from the fingerprint sensor, converting the analog signal into a plurality of digital signals; converting the digital signals into a plurality of digital signals pixel signals; and normalizing the pixel signals to generate a plurality of normalized pixel signals, wherein the pixel signals are an N×M matrix, N and M are both natural numbers, and the pixel signals of each row include N pixel signals, the normalizing step includes: calculating a pixel average value of each row, wherein the pixel average value is calculated based on less than N of the pixel signals; and corresponding to the row The N pixel signals of , respectively, are subtracted from the pixel average value to generate N normalized pixel signals.

In one example, the step of calculating the pixel average value includes: obtaining a base value of the N pixel signals corresponding to the row; obtaining a minimum pixel signal with a maximum amplitude difference from the base value; obtaining the base value and the base value a maximum pixel signal with a minimum amplitude difference; and averaging the minimum pixel signal and the maximum pixel signal to obtain the pixel average.

In one example, the step of calculating the pixel average value includes: obtaining a base value of the N pixel signals corresponding to the row; obtaining a minimum value pixel signal with a maximum amplitude difference from the base value and the minimum value of the pixel signal with the minimum value. A value of the pixel signals adjacent to the pixel signal position is averaged to obtain a valley average; a maximum pixel signal with a minimum amplitude difference from the base value and a portion adjacent to the maximum pixel signal position are obtained. The pixel signals are averaged to obtain a peak average; and the trough average and the peak average are averaged to obtain the pixel average.

In one example, the step of calculating the pixel average value includes: obtaining a base value of the N pixel signals corresponding to the row; obtaining a minimum pixel signal with a maximum amplitude difference from the base value and a sum less than At least one pixel signal with the largest amplitude difference is averaged to obtain a valley average; a maximum pixel signal with the smallest amplitude difference from the base value and at least one pixel signal larger than the minimum amplitude difference are obtained and averaged to obtain a peak average; and averaging the trough average and the peak average to obtain the pixel average.

According to the above, a fingerprint signal processing method for a fingerprint sensor, comprising: receiving a background correction control signal by a correction control circuit and receiving an analog signal from the fingerprint sensor, and converting the analog signal into a complex number and storing the digital signals by a temporary storage circuit; converting the digital signals into a plurality of pixel signals by an interpretation circuit; wherein, when the background correction control signal is at a high level , the calibration control circuit reads a plurality of calibration parameters from the temporary storage circuit to update a plurality of offsets of the digital signal.

In one example, the fingerprint signal processing method further receives the analog signal through a plurality of analog-to-digital converters, and converts the analog signal into the digital signal according to the corresponding offsets respectively; and corrects the analog signal by an offset The circuit receives the background correction control signal, a target parameter and the correction parameters, and when the background correction control signal is at the high level, updates the offsets according to the target parameter or the correction parameters or a combination of the above, to The corrected offsets are generated.

In one example, when the background correction control signal is at a low level, the offsets are before update or after correction.

In one example, the fingerprint signal processing method further includes normalizing the pixel signals by a normalization circuit to generate a plurality of normalized pixel signals, wherein the pixel signals are an N×M matrix, N and M All are natural numbers, and the pixel signals of each row include N pixel signals. The normalization step includes: calculating a pixel average value of each row, wherein the pixel average value is based on less than N of these images. and the N pixel signals corresponding to the row are respectively subtracted from the pixel average value to generate N normalized pixel signals.

The content of the present invention will be explained by the following examples, which are not intended to limit the implementation of the present invention in any specific environment, application or special manner as described in the embodiments. Therefore, the description of the embodiments is only for the purpose of illustrating the present invention, rather than limiting the present invention. It should be noted that, in the following embodiments and drawings, elements not directly related to the present invention are omitted and not shown, and the dimensional relationships among the elements in the drawings are only for easy understanding, not for limiting the actual scale.

FIG. 1 is a schematic diagram of a fingerprint signal processing system 100 according to some embodiments of the present application. Please refer to FIG. 1 , the fingerprint signal processing system 100 includes a calibration control circuit 110 , a temporary storage circuit 120 , an interpretation circuit 130 and a normalization circuit 140 . The temporary storage circuit 120 is electrically connected to the calibration control circuit 110 and the decoding circuit 130 , and the decoding circuit 130 is electrically connected to the normalization circuit 140 . In this embodiment, the fingerprint signal processing system 100 may be a single integrated circuit (IC) or at least a part of an application-specific integrated circuit (ASIC), or include a module that is integrated by wires, active and passive components, ICs and ASICs or part of a packaged component. The temporary storage circuit 120 may be a memory with a storage function.

Continuing to refer to FIG. 1 , the fingerprint signal processing system 100 is connected to a fingerprint sensor (not shown in FIG. 1 ) and receives an analog signal (IMG) from the fingerprint sensor. In this embodiment, a fingerprint sensor with an encoding function is used. If a detector is used, such as Glass Sensor Encoder (GSE), the analog signal (IMG) is the encoded signal. For example, in a fingerprint sensor with encoding function, the original signal is converted into an encoded analog signal IMG, please refer to "Table 1" and "Table 2". "Table 1" assumes that the original signal is 4x4 image data, and "Table 2" is the 4x4 encoded image data generated after the original signal is encoded by the fingerprint sensor. Secondly, the encoded image data Y00 is the average value of the sum of X00, X10, X20 and X30, Y01 is the average value of the sum of X01, X11, X21 and X31, and Y02 is the sum of X02, X12, X22 and X32 After the average value, Y03 is the average value of the sum of X03, X13, X23 and X33. Therefore, in the encoded image data, the first bit of each line (column) is the average value of each line (column) data in the original image data, but the encoding method of the fingerprint sensor is not limited to this. The present invention utilizes the first row (row) signal data Y00, Y01, Y02, and Y03 of the encoded "Table 2" to correct the analog offset. It can be understood that when the original signal is 16x16 image data, the data values in the first row (row) of the encoded "Table 2" are Y00, Y01, Y02..., Y0E and Y0F. "Table 1" X00 X01 X02 X03 X10 X11 X12 X13 X20 X21 X22 X23 X30 X31 X32 X33 "Table 2" Y00 Y01 Y02 Y03 Y10 Y11 Y12 Y13 Y20 Y21 Y22 Y23 Y30 Y31 Y32 Y33

Continuing to refer to FIG. 1 , in this embodiment, the calibration control circuit 110 includes a plurality of analog-to-digital converters (ADCs) 111 and an offset calibration circuit 112 . The offset correction circuit 112 is electrically connected to the analog-to-digital converter 111 . The analog-to-digital converter 111 receives the analog signal IMG, and the offset correction circuit 112 receives the background correction control signal CTL, the target parameter TAR and the correction parameter CAL. The fingerprint signal processing system 100 further includes a wiring 150, and the wiring 150 is electrically connected to the offset Correction circuit 112 and temporary storage circuit 120 . In the present embodiment, the offset correction circuit 112 is used for reading the calibration parameter CAL stored in the temporary storage circuit 120 from the temporary storage circuit 120 through the wire 150 .

FIG. 2 is a flowchart of a fingerprint signal processing method 200 according to some embodiments of the present application. Please refer to FIG. 1 and FIG. 2 together. In an embodiment, the fingerprint signal processing method 200 shown in FIG. 2 can be applied to the fingerprint signal processing system 100 of FIG. 1. In step S210, the calibration control circuit 110 receives the background calibration The control signal CTL and the analog signal IMG are received from the fingerprint sensor, and the calibration control circuit 110 converts the analog signal IMG into a plurality of digital signals DS. Next, in step S220, the temporary storage circuit 120 stores the digital signal DS. In this embodiment, step S210 may include steps S211 to S213, and FIG. 3 is a flowchart of step S210 according to some embodiments of the present application. Please refer to FIG. 1 to FIG. 3 together. The fingerprint signal processing method 200 further executes step S211, and the offset correction circuit 112 determines whether the background correction control signal CTL is at a high level. If the background correction control signal CTL is at a high level, it means that the If the invention wants to enter a background adjustment mode, step S212 is further executed to update the offset of the analog-to-digital converter according to the target parameter TAR, the calibration parameter CAL or the above two, for example, to form the corrected offset in the digital signal by means of compensation quantity. For example, the corrected offset is formed according to the difference between the target parameter TAR and the correction parameter CAL to compensate the offset of the analog-to-digital converter. In this embodiment, when the background correction control signal CTL is at a high level, the offset correction circuit 112 is used to read the correction parameter CAL (that is, each column) stored in the temporary storage circuit 120 through the wiring 150 . ) of the average value Y00, Y01, ...), using the correction parameter CAL to correct the offset of the analog-to-digital converter.

Continuing to refer to FIGS. 1 to 3 , in general, the calibration of the analog-to-digital converter is performed at startup, so the firmware enables the background calibration control signal CTL at startup, and the offset correction circuit 112 performs the calibration according to the initial digital signal DS Offset correction. The offset correction circuit 112 reads the digital signals of the first column of the digital signals stored in an encoding matrix (two-dimensional matrix) through the wiring 150 as the correction parameters CAL for correcting the offsets of the analog-digital converters 111 . It is worth noting that the temporary storage circuit 120 is composed of M memory arrays, the total number of storage units in the memory array is N, M and N are both natural numbers, and N is 256 bytes. Therefore, the digital signal of the first row refers to the digital signal DS stored in the memory array of the first row, and the digital signal of the first row has M bytes. As mentioned above, in the offset correction circuit 112 , the first row (row) of digital signals is composed of the average value of the original signal (ie, the signal X before encoding) of each row (column). Continuing the examples in Table 1 and Table 2, the encoded image data Y00 is the average value of the sum of X00, X10, X20 and X30, and Y01 is the average value of the sum of X01, X11, X21 and X31 , and so on. Therefore, the digital signal DS in the memory array of the first row (Y00, Y01, Y02...) is calculated according to the average value of the pixel signal of each row (column) before encoding, and of course it can also reflect the data before encoding. Background mean for each row (column). In this way, the offset of each analog-to-digital converter 111 can be corrected according to the average value of the digital signals DS of each column by using the digital signal DS in the first row of the memory array as the calibration parameter CAL.

Continuing to refer to Figures 1 to 3, the target parameter TAR is used to adjust the brightness of the image background. For example, optionally, the correction offset can be expressed as the difference between the target parameter TAR and the correction parameter CAL multiplied by a ratio (such as 1/4 or others), in this way, with the continuous scanning of the image to update the calibration parameter CAL recursively, the calibration parameter CAL will gradually approach the target parameter TAR, which means that the average value of the background image has approached the target parameter TAR. .

Continuing to refer to FIGS. 1 to 3 , if the offset correction circuit 112 in step S211 determines that the background correction control signal CTL is at a low level, it means that it is not the background adjustment mode at this time, it may be a fingerprint reading or fingerprint pressing mode. , step S213 is further executed, at this time, the offset in the analog-digital converter 111 remains unchanged, that is, the analog-digital converter 111 adjusts the offset according to the previous background adjustment or the analog-digital conversion is its own. Offset (if no background adjustment is performed at startup), converts the analog signal IMG to the digital signal DS. In this embodiment, when the background correction control signal CTL is at a low level, the offset of the analog-to-digital converter 111 is not compensated. For example, when reading a fingerprint, the firmware can disable the background correction control signal CTL, and the offset of the analog-to-digital converter 111 has been calibrated at startup, so the analog-to-digital converter 111 will The analog signal IMG is converted into a digital signal DS according to the calibration completed when the device is turned on.

1-3, in step S230, the decoding circuit 130 converts the digital signal DS into a plurality of pixel signals PS. In this embodiment, in step S210, the analog-to-digital converter 111 converts the analog signal into the digital signal DS according to the offset of the offset correction circuit by the coding matrix from the sensor, and then in step S230, the solution is The decoding circuit 130 converts the digital signal into the pixel signal PS through the decoding matrix. The digital signal DS stored in the memory array of the first row will be regarded as 0 or discarded during the decoding process. Since the data stored in the first byte of each row (column) may still be distorted, the reason for the distortion is When there is a finger, the average burst will cause oversaturation, so the decoded pixel signal PS will have an offset. Therefore, the fingerprint signal processing method 200 further executes step S240 to normalize the pixel signal PS by the normalization circuit 140 to generate a plurality of normalized pixel signals. In this embodiment, the pixel signal PS is an N×M matrix, and both N and M are natural numbers. Taking N equal to 256 as an example, calculate the pixel average value of the pixel signal PS of each row. The pixel signal PS of each row includes 256 pixel signals PS, and the 256 pixel signals PS are respectively averaged with the pixels. The values are subtracted to produce 256 normalized pixel signals. In this embodiment, the pixel average value is calculated according to the maximum pixel signal and the minimum pixel signal among the 256 pixel signals PS. In addition, the offset provided by the offset correction circuit may be a digital starting offset of 0 without performing background adjustment.

Based on the above, please refer to FIG. 4 , which is a schematic diagram of a line of pixel signals according to some embodiments of the present application. As shown in FIG. 4 , a line of pixel signals includes a plurality of peaks PH and a plurality of valleys PL, including a base value PS1 of a direct current (DC) starting value. This normalization method is to find the best peak PHB (meaning the minimum pixel signal, the amplitude difference between the peak PH and the base value PS1 is the largest) and the best trough PLB (meaning the maximum pixel signal) among the multiple peaks PH , the amplitude difference between the trough PL and the base value PS1 is the smallest), add the minimum pixel signal represented by the best peak PHB and the maximum pixel signal represented by the best trough PLB, and then divide by 2 to obtain the line pixel average of . Then, the N pixel signals are respectively subtracted from the pixel average value to generate N normalized pixel signals. In this way, the offset generated at the time of decoding can be corrected. It is worth noting that, after the normalized pixel signal is generated, the normalized pixel signal can be sent to the algorithm side as the input signal of the fingerprint identification algorithm.

Continuing to refer to FIG. 4 , it should be noted that the present invention is not limited to taking the result obtained by the first method of adding and averaging the minimum pixel signal and the maximum pixel signal as the pixel average value. The second method is to add a plurality of troughs PL and divide by the number of samples, and add a plurality of peaks PH and divide by the number of samples, and then average the two to obtain an average pixel value, where the plurality of troughs PL Including the best trough PLB, and the plurality of peaks PH including the best peak PHB, the sum of the peaks and troughs of the pixel signal whose total number of sampling is less than one line. For example, in a line of pixel signals, take the average of the top five pixel signals (the top five with the smallest amplitude difference between the trough PL and the base value PS1) (the average of the troughs) and the top five small values (including the peak PH and the base value PS1). The average value of the top five (the peak average) with the largest amplitude difference of the value PS1 is divided by 2 to obtain the pixel average value in the present invention. In this method, the top five-value pixel signals include the best trough PLB and have amplitude order, and the top five small-value pixel signals include the best peak PHB and have amplitude order. Secondly, the sampling numbers of the peak PH and the trough PL can be the same or different. In another example of the second method, first obtain the average including the best trough PLB and one or more troughs PL adjacent to the best trough PLB (trough average), and then obtain the average including the best peak PHB and the best trough PLB. The average value of one or more peaks PH adjacent to the peak PHB (peak average), and finally the average value of both the valley average and the peak average is calculated as the pixel average required for normalization. In this example, the sampled plurality of troughs PL include the best trough PLB and have a positionally adjacent association with the best trough PLB, and the sampled plurality of peaks PH include the best wave peak PHB and have the best wave peak PHB and have a position adjacent to the best wave trough PLB. correlation.

FIG. 5 is a schematic diagram of a second fingerprint signal processing system according to some embodiments of the present application. Referring to FIG. 1 and FIG. 5 , the fingerprint signal processing system 300 includes a conversion circuit 310 , a temporary storage circuit 320 , an interpretation circuit 330 and a normalization circuit 140 . The fingerprint signal processing system 300 is connected to a fingerprint sensor (not shown in FIG. 1 ) and receives an analog signal IMG' from the fingerprint sensor, wherein the analog signal IMG' may be unencoded. The analog signal IMG' is converted into a digital signal DS' after analog-to-digital conversion by the analog-to-digital converter 111 of the conversion circuit 310. The digital signal DS' is sent to the temporary storage circuit 320 for storage, and the decoding circuit 330 converts the digital signal DS' through the decoding matrix. The pixel signal PS' is converted into, and then the normalization circuit 140 normalizes the pixel signal PS' to generate a plurality of normalized pixel signals.

FIG. 6 is a flowchart of a second fingerprint signal processing method according to some embodiments of the present application. The system shown in FIG. 5 can be implemented through the process of FIG. 6 . Please refer to FIG. 6 , the fingerprint signal processing method 400 can be implemented in a single IC or IC package including the fingerprint signal processing system 300 . In step S410 , the conversion circuit 310 receives the analog The signal IMG' and the analog signal IMG' are converted into a plurality of digital signals DS'. Next, in step S420, the temporary storage circuit 320 stores the digital signal DS'. In step S430, the decoding circuit 330 converts the digital signal DS' into a plurality of pixel signals PS'. In the temporary storage circuit 320, the digital signal DS' stored in the memory array of the first row will be regarded as 0 or discarded during the decoding process. Then, in step S240, the normalization circuit 140 normalizes the pixel signal PS' to generate a plurality of normalized pixel signals.

It should be noted that the fingerprint signal processing system in FIG. 1 can also be designed without the normalization circuit 140, and directly transmit the pixel signal PS to the back-end calculation, as shown in FIG. 7, that is, the fingerprint signal processing system 500 performs background correction , so steps S210 to S230 in FIG. 2 can be performed in combination. It can be understood that each circuit in the system of the present invention can be implemented in a semiconductor structure through a semiconductor process.

It can be seen from the above-mentioned embodiments of the present case that the main problem is to improve the previous problem of slowing down the speed of fingerprint data acquisition by performing correction through the judgment of the algorithm. To correct the offset of the analog digital converter, and then correct the offset generated during decoding by calculating the pixel average value of each line, and do not need to be corrected through the algorithm. The effect of taking fingerprint data speed. Furthermore, the average value of the pixel signal calculated by using the peaks and valleys of the pixel signal is more accurate than the previous algorithm for obtaining the average value and is not easily affected by the fingerprint pressing area.

In addition, the above illustrations include sequential exemplary steps, but the steps do not have to be performed in the order shown. It is within the contemplation of this disclosure to perform the steps in a different order. These steps may be added, replaced, changed order and/or omitted as appropriate within the spirit and scope of the embodiments of the present disclosure.

Although this case has been disclosed above in terms of implementation, it is not intended to limit this case. Anyone who is familiar with this technique can make various changes and modifications without departing from the spirit and scope of this case. Therefore, the scope of protection in this case should be considered later. The scope of the attached patent application shall prevail.

100, 300, 500: Fingerprint Signal Processing System 110: Correction control circuit 111: Analog-to-digital converters 112: Offset correction circuit 120, 320: Temporary circuit 130, 330: Interpreting circuits 140: Normalized Circuits 150: line CTL: Background correction control signal TAR: target parameter CAL: Calibration parameter IMG, IMG’: analog signal DS, DS’: digital signal PS, PS': pixel signal PS1: base value PH: crest PL: trough PHB: Best crest PLB: Best Valley 200, 400: Fingerprint signal processing method 310: Conversion circuit S210~S240, S211~S213, S410~S430: Steps

FIG. 1 is a schematic diagram of a first fingerprint signal processing system according to some embodiments of the present application. FIG. 2 is a flowchart of a first fingerprint signal processing method according to some embodiments of the present application. FIG. 3 is a flowchart of step S210 according to some embodiments of the present application. FIG. 4 is a schematic diagram of a line pixel signal according to some embodiments of the present application. FIG. 5 is a schematic diagram of a second fingerprint signal processing system according to some embodiments of the present application. FIG. 6 is a flowchart of a second fingerprint signal processing method according to some embodiments of the present application. FIG. 7 is a schematic diagram of a third fingerprint signal processing system according to some embodiments of the present application.

100: Fingerprint Signal Processing System

110: Correction control circuit

111: Analog-to-digital converters

112: Offset correction circuit

120: Temporary storage circuit

130: Interpretation Circuit

140: Normalized Circuits

150: line

CTL: Background correction control signal

TAR: target parameter

CAL: Calibration parameter

IMG: analog signal

DS: digital signal

PS: pixel signal

Claims (20)

A fingerprint signal processing system for a fingerprint sensor, comprising: a calibration control circuit, which receives a background calibration control signal, receives an encoded analog signal from the fingerprint sensor, and converts the encoded analog signal into a plurality of a digital signal, wherein the encoded analog signal is an original image data read by the fingerprint sensor; a temporary storage circuit, which is electrically connected to the calibration control circuit and stores the digital signals, wherein the digital signals are stored in a Two-dimensional matrix storage, a first row (row) of the two-dimensional matrix includes a plurality of correction parameters, wherein when the background correction control signal is a high level, the correction control circuit reads from the temporary storage circuit The plurality of calibration parameters are used to update the plurality of offsets of the digital signals; and an interpretation circuit is electrically connected to the temporary storage circuit for converting the digital signals into a plurality of pixel signals. The fingerprint signal processing system of claim 1, further comprising a normalization circuit electrically connected to the decoding circuit, which normalizes the pixel signals to generate a plurality of normalized pixel signals. The fingerprint signal processing system according to claim 1 or 2, wherein the calibration control circuit comprises: a plurality of analog-to-digital converters for receiving the encoded analog signal, and the analog-to-digital converters respectively according to the corresponding offsets The encoded analog signal is converted into the digital signals; and an offset correction circuit is electrically connected to the analog-to-digital converters, the offset correction circuit receives the background correction control signal, a target parameter and the correction parameters, when the When the background correction control signal is at the high level, the offsets are updated according to the target parameter or the correction parameters or a combination thereof, thereby generating the corrected offsets. The fingerprint signal processing system of claim 3, wherein when the background correction control signal is at a low level, the offsets are either before updating or after being corrected. The fingerprint signal processing system according to claim 3, further comprising a wire electrically connected to the offset correction circuit and the temporary storage circuit. The fingerprint signal processing system of claim 5, wherein the offset correction circuit is configured to read the correction parameters stored in the temporary storage circuit from the temporary storage circuit through the wiring, each of the correction parameters is the average value of each line of data in the original image data. The fingerprint signal processing system according to claim 2, wherein an encoded signal of the temporary storage circuit is an N×M matrix, N and M are both natural numbers, and the decoding circuit generates the N×M matrix For the pixel signals, each row of the N x M matrix includes N of the pixel signals, the normalization circuit calculates a pixel average value of the N pixel signals corresponding to each row, and assigns the corresponding The N pixel signals of , respectively, are subtracted from the pixel average value to generate N normalized pixel signals, and the pixel average value is calculated based on less than N of the pixel signals. The fingerprint signal processing system according to claim 7, wherein the average value of the pixels in the row is to calculate the average of an optimal peak pixel signal and an optimal trough pixel signal among the corresponding N pixel signals obtained, and wherein the amplitude difference between the optimal peak pixel signal and a base value of the pixel signals in the row is greater than the other pixel signals in the row, and the optimal trough pixel signal is different from the row. The amplitude difference of the base value of the pixel signals of the row is smaller than the other pixel signals of the row. The fingerprint signal processing system according to claim 7, wherein the average value of the pixels in the row is to calculate the average of an optimal peak pixel signal and an optimal trough pixel signal among the corresponding N pixel signals obtained; The optimal peak pixel signal at least includes a maximum pixel signal with the largest amplitude difference from a base value of the pixel signals in the row and the average of the other part of the pixel signals; and the optimal valley image The pixel signal at least includes a minimum pixel signal with the smallest amplitude difference from a base value of the pixel signals in the row and the average of the other pixel signals. A fingerprint signal processing method for a fingerprint sensor, comprising: receiving an analog signal from the fingerprint sensor, converting the analog signal into a plurality of digital signals; converting the digital signals into a plurality of pixel signals ; and normalize the pixel signals to generate a plurality of normalized pixel signals, wherein the pixel signals are an N×M matrix, N and M are both natural numbers, and the pixel signals of each row include N pictures pixel signal, the normalization step includes: calculating a pixel average value of each row, wherein the pixel average value is calculated based on less than N of the pixel signals; and the N corresponding to the row The pixel signals are respectively subtracted from the pixel average to generate N normalized pixel signals. The fingerprint signal processing method according to claim 10, wherein the step of calculating the pixel average value comprises: obtaining a base value of the N pixel signals corresponding to the row; obtaining a signal having the largest amplitude difference with the base value a minimum pixel signal; obtaining a maximum pixel signal with a minimum amplitude difference from the base value; and averaging the minimum pixel signal and the maximum pixel signal to obtain the pixel average value. The fingerprint signal processing method according to claim 10, wherein the step of calculating the pixel average value comprises: obtaining a base value of the N pixel signals corresponding to the row; obtaining a signal having the largest amplitude difference with the base value A minimum pixel signal and a portion of the pixel signals adjacent to the minimum pixel signal are averaged to obtain a valley average; a maximum pixel signal with a minimum amplitude difference from the base value is obtained and the The pixel signals adjacent to the position of the maximum pixel signal are averaged to obtain a peak average; and the trough average and the peak average are averaged to obtain the pixel average. The fingerprint signal processing method according to claim 10, wherein the step of calculating the pixel average value comprises: obtaining a base value of the N pixel signals corresponding to the row; obtaining a signal having the largest amplitude difference with the base value A minimum pixel signal and at least one pixel signal smaller than the maximum amplitude difference are averaged to obtain a valley average; a maximum pixel signal with a minimum amplitude difference from the base value and at least one larger than the minimum amplitude difference are obtained. A pixel signal is averaged to obtain a peak average; and the trough average and the peak average are averaged to obtain the pixel average. A fingerprint signal processing method for a fingerprint sensor, comprising: receiving a background correction control signal through a correction control circuit and receiving an analog signal from the fingerprint sensor, and converting the analog signal into a plurality of digital signals ; store the digital signals by a temporary storage circuit; and convert the digital signals into a plurality of pixel signals by an interpretation circuit; Wherein, when the background correction control signal is at a high level, the correction control circuit reads a plurality of correction parameters from the temporary storage circuit to update a plurality of offsets of the digital signal; The converter receives the analog signal, and converts the analog signal into the digital signals according to the corresponding offsets respectively; and receives the background correction control signal, a target parameter and the corrections through an offset correction circuit parameters, when the background correction control signal is at the high level, the offsets are updated according to the target parameter or the correction parameters or a combination thereof to generate the corrected offsets. The fingerprint signal processing method as claimed in claim 14, wherein when the background correction control signal is at a low level, the offsets are either before updating or after being corrected. The fingerprint signal processing method according to claim 14, further comprising: reading the correction parameters stored in the temporary storage circuit from the temporary storage circuit through a wiring by the offset correction circuit; wherein, the first A row of digital signals consists of the average value of the original digital signals of each row before encoding. The fingerprint signal processing method of claim 14, further comprising normalizing the pixel signals by a normalization circuit to generate a plurality of normalized pixel signals, wherein the pixel signals are an N×M matrix, Both N and M are natural numbers, and the pixel signals of each row include N pixel signals. The normalization step includes: calculating a pixel average value of each row, wherein the pixel average value is based on less than N pixel signals. The pixel signals are calculated and obtained; and the N pixel signals corresponding to the row are respectively subtracted from the pixel average value to generate N normalized pixel signals. The fingerprint signal processing method according to claim 17, wherein the step of calculating the pixel average value comprises: obtaining a base value of the N pixel signals corresponding to the row; Obtaining a minimum pixel signal with the maximum amplitude difference from the base value; obtaining a maximum pixel signal with the minimum amplitude difference with the base value; and averaging the minimum pixel signal and the maximum pixel signal. The fingerprint signal processing method according to claim 17, wherein the step of calculating the pixel average value comprises: obtaining a base value of the N pixel signals corresponding to the row; obtaining a signal with the largest amplitude difference from the base value A minimum pixel signal and a portion of the pixel signals adjacent to the minimum pixel signal are averaged to obtain a valley average; a maximum pixel signal with a minimum amplitude difference from the base value is obtained and the The pixel signals adjacent to the position of the maximum pixel signal are averaged to obtain a peak average; and the trough average and the peak average are averaged to obtain the pixel average. The fingerprint signal processing method according to claim 17, wherein the step of calculating the pixel average value comprises: obtaining a base value of the N pixel signals corresponding to the row; obtaining a signal with the largest amplitude difference from the base value A minimum pixel signal and at least one pixel signal smaller than the maximum amplitude difference are averaged to obtain a valley average; a maximum pixel signal with a minimum amplitude difference from the base value and at least one larger than the minimum amplitude difference are obtained. A pixel signal is averaged to obtain a peak average; and the trough average and the peak average are averaged to obtain the pixel average.

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