WO2017080310A1 - 指纹图像处理方法、装置和终端设备 - Google Patents
指纹图像处理方法、装置和终端设备 Download PDFInfo
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- WO2017080310A1 WO2017080310A1 PCT/CN2016/099361 CN2016099361W WO2017080310A1 WO 2017080310 A1 WO2017080310 A1 WO 2017080310A1 CN 2016099361 W CN2016099361 W CN 2016099361W WO 2017080310 A1 WO2017080310 A1 WO 2017080310A1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/12—Fingerprints or palmprints
- G06V40/1347—Preprocessing; Feature extraction
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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- G06V10/22—Image preprocessing by selection of a specific region containing or referencing a pattern; Locating or processing of specific regions to guide the detection or recognition
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Definitions
- the module quality is controlled according to the number of bad points. If the number of bad points exceeds the preset threshold, the product cannot be shipped; and another control parameter of the dead point is that the number of bad points in any unit area cannot exceed Threshold, such a control range is to prevent the dead pixels from being too concentrated. Too concentrated will cause a certain area of the image to be completely black or white and unrecognizable. But even with this control, the dead pixels of the product fingerprint module in the user's hand are always present.
- the present invention aims to solve at least one of the technical problems in the related art to some extent. Therefore, the first object of the present application is to provide a fingerprint image processing method, which realizes the recognition and correction of the dead pixels on the fingerprint module during the fingerprint recognition process, and improves the fingerprint image quality and the fingerprint recognition rate.
- a third object of the present invention is to provide a terminal device.
- a fourth object of the present application is to propose a terminal device.
- a fifth object of the present invention is to provide a non-volatile computer storage medium.
- the first aspect of the present application provides a fingerprint image processing method, including: when a fingerprint is input, generating fingerprint image data corresponding to the contact finger by using a capacitive sensor; and marking a fingerprint image that does not belong to the preset data range.
- the data is a dead point; the fingerprint image data of the dead point is corrected according to the data range; and the corresponding fingerprint image is generated according to the corrected fingerprint image data.
- the second aspect of the present application provides a fingerprint image processing apparatus, including: a generating module, configured to generate fingerprint image data corresponding to a contact finger by a capacitive sensor when the fingerprint is entered; and an identification module, configured to Marking the fingerprint image data that is not in the preset data range as a bad point; the correction module is configured to correct the fingerprint image data of the dead point according to the data range; and the processing module is configured to generate a corresponding image according to the corrected fingerprint image data Fingerprint image.
- a generating module configured to generate fingerprint image data corresponding to a contact finger by a capacitive sensor when the fingerprint is entered
- an identification module configured to Marking the fingerprint image data that is not in the preset data range as a bad point
- the correction module is configured to correct the fingerprint image data of the dead point according to the data range
- the processing module is configured to generate a corresponding image according to the corrected fingerprint image data Fingerprint image.
- the third aspect of the present application provides a terminal device, including: a fingerprint module having a capacitive sensor, and a fingerprint image processing device as described above.
- the fourth aspect of the present application provides a terminal device, including: a housing, a processor, a memory, a circuit board, and a power supply circuit, wherein the circuit board is disposed in the housing Inside the space, the processor and the memory are disposed on the circuit board; the power circuit is configured to supply power to each circuit or device of the mobile terminal; the memory is configured to store executable program code;
- the processor runs a program corresponding to the executable program code by reading executable program code stored in the memory, for performing the following steps: when the fingerprint is entered, generating a fingerprint corresponding to the contact finger by using the capacitive sensor Image data; marking fingerprint image data that does not belong to the preset data range as a bad point; correcting the fingerprint image data of the bad point according to the data range; and generating a corresponding fingerprint image according to the corrected fingerprint image data.
- a fifth aspect of the present invention provides a non-volatile computer storage medium storing one or more programs, when the one or more programs are executed by a device, causing the device A fingerprint image processing method in accordance with an embodiment of the first aspect of the present invention is performed.
- the invention realizes the recognition and correction of the dead pixels on the fingerprint module in the process of fingerprint recognition, and improves the fingerprint image quality and the fingerprint recognition rate.
- Figure 1 is a schematic diagram of a fingerprint image containing a dead pixel
- FIG. 2 is a flowchart of a fingerprint image processing method according to an embodiment of the present application.
- 3 is a three-dimensional figure formed by simulating fingerprint image data with a finger peak valley
- FIG. 6 is a flowchart of a fingerprint image processing method according to another embodiment of the present application.
- FIG. 7 is a schematic structural diagram of a fingerprint image processing apparatus according to an embodiment of the present application.
- FIG. 8 is a schematic structural diagram of a fingerprint image processing apparatus according to another embodiment of the present application.
- FIG. 9 is a schematic structural diagram of a terminal device according to an embodiment of the present application.
- FIG. 2 is a flow chart of a fingerprint image processing method according to an embodiment of the present application.
- the fingerprint image processing method includes:
- Step 101 When the fingerprint is entered, the fingerprint image data corresponding to the contact finger is generated by the capacitance sensor.
- the fingerprint image processing method provided in this embodiment is configured in a terminal device that supports the fingerprint module for fingerprint recognition as an example.
- a terminal device that supports the fingerprint module for fingerprint recognition
- the capacitance sensor determines the specific distribution of the finger valley and the finger peak according to the magnitude of the capacitance formed by the finger valley and the finger peak and the capacitance sensor.
- the specific working principle is: by pre-charging the capacitive sensor on each pixel to the reference voltage, when the finger touches the capacitive sensor, since the finger peak is convex, the finger valley is concave, therefore, the finger peak and the finger valley are The distance of the capacitive sensor plane is different.
- the capacitance value and the distance According to the relationship between the capacitance value and the distance, different capacitance values are formed at the positions of the finger peaks and the finger valleys. Then, the discharge is performed by the discharge current, and since the capacitance values corresponding to the finger peak and the finger valley are different, the corresponding discharge speeds are also different.
- the peak is close to the capacitive sensor, the capacitance is high, the discharge is slow, the valley is far from the capacitance sensor, the capacitance is low, and the discharge is faster.
- the position of the finger peak and the finger valley can be determined, thereby generating the number of fingerprint images corresponding to the contact finger. according to.
- Step 102 Mark the fingerprint image data that does not belong to the preset data range as a dead pixel.
- the dielectric constant of the impurity and the cover plate cannot be uniformly compared, some of them are high and low, and some appear black and white.
- the dead point is fixed, that is, the position of the dead point on the fingerprint image is fixed, and the white point or black point of the dead point is analyzed from the image to be a clear position.
- FIG. 3 is a three-dimensional graph having a peak-to-finger valley formed by simulating fingerprint image data.
- each fingerprint image data corresponding to the contact finger forms a three-dimensional map.
- the data is almost the same, but there are some points that are abnormally high or abnormally low.
- the fingerprint image data corresponding to the bad point is a range value far beyond the preset upper and lower limits. For example, although a lake has ripples, it is in the normal range. If there is a vortex or a high wave, it is a bad point.
- 4 is a schematic diagram of fingerprint image data. Referring to Figure 4, for each parallel line, the adjacent data is very close because of the layout trace, but some points on the line are very high or low or bad.
- the fingerprint image data is detected according to the preset data range, and the fingerprint image data that does not belong to the preset data range is marked as a bad point.
- the preset data range may be determined according to the historical sample set of the fingerprint image data, or may be adjusted according to the actual application situation, which is not limited in this embodiment.
- Step 103 Correct the fingerprint image data of the dead point according to the data range.
- the fingerprint image data of the dead pixel is corrected according to the data range, so that the corrected fingerprint image data belongs to a preset data range. It should be noted that there are many ways to correct the fingerprint image data of the dead pixels, which can be selected according to the actual application needs, as follows:
- the fingerprint image data larger than the preset data range is reduced, so that the subtracted fingerprint image data belongs to the data range, or
- the fingerprint image data of the dead pixels is updated by applying an average value of the fingerprint image data belonging to the data range.
- Step 104 Generate a corresponding fingerprint image according to the corrected fingerprint image data.
- the fingerprint image data of the dead point is corrected according to the preset data range, all the fingerprint image data belong to a preset data range, and then the pixel corresponding to each capacitive sensor according to the corrected fingerprint image data. Generate a corresponding fingerprint image on it.
- FIG. 5 is a schematic diagram of a fingerprint image.
- the left side view of FIG. 5 is a fingerprint image generated according to original fingerprint image data of a finger in contact with the fingerprint module, which is visible from the left side view.
- the fingerprint image data of the place exceeds the preset data range, that is, a bad point, which is expressed as a white point, and the fingerprint image data is corrected according to the preset data range, and the fingerprint image generated according to the corrected fingerprint image data, such as
- the effect of the performance is that the white point of the white point will become the same average as the surrounding, forming a black point, and naturally forming a line, that is, a peak, so that the previous dead point is generated.
- the breakpoint fingerprint image is repaired and displayed normally.
- the fingerprint image data corresponding to the contact finger is generated by the capacitive sensor, and the fingerprint image data that does not belong to the preset data range is marked as a bad point, and the bad is corrected according to the data range.
- the fingerprint image data of the point generates a corresponding fingerprint image based on the corrected fingerprint image data.
- FIG. 6 is a flowchart of a fingerprint image processing method according to another embodiment of the present application.
- the fingerprint image processing method includes:
- Step 201 Acquire a difference between an average value of the fingerprint image sample data and a finger valley peak, and set the data range according to the average value and the difference value.
- Step 202 When the fingerprint is entered, the fingerprint image data corresponding to the contact finger is generated by the capacitance sensor;
- Step 203 marking fingerprint image data that does not belong to the preset data range as a bad point
- Step 204 Apply an average value of fingerprint image data belonging to the data range, update fingerprint image data of the dead pixel, and store the corrected fingerprint image data of the dead pixel;
- Step 205 Generate a corresponding fingerprint image according to the corrected fingerprint image data.
- Step 206 When the finger touches the capacitive sensor corresponding to the bad point, the corrected fingerprint image data is given.
- the preset data range is determined according to the acquired fingerprint image sample data, and the average value of the fingerprint image sample data and the difference of the finger valley peak are first acquired, and then the data range is set according to the average value and the difference value.
- An example is as follows:
- the mean value of the fingerprint image sample data is 1300, and the difference between the peak and the finger valley is also within 300, that is, the normal underlying data is between 1000 and 1600, so the upper limit of the set data range is 2000, the lowest The lower limit is 500.
- the fingerprint image data corresponding to the contact finger is generated by the capacitive sensor, and then the fingerprint image data is detected according to the preset data range, and the fingerprint image data that does not belong to the preset data range is marked as a bad point, when the upper and lower limits are exceeded, It is determined that the position of the data with the point is a bad point.
- the underlying data value of the bad point is not used for image generation, but is directly assigned to the pre-stored and dead pixels. Corresponding modified fingerprint image data, and then a fingerprint image is generated.
- the average value of the fingerprint image sample data and the difference of the finger valley peak are obtained, and the data range is set according to the average value and the difference, and when the fingerprint is entered, the capacitor is used.
- the sensor generates fingerprint image data corresponding to the contact finger, marks the fingerprint image data that does not belong to the preset data range as a bad point, applies an average value of the fingerprint image data belonging to the data range, and updates the fingerprint image data of the bad point and
- the storing generates a corresponding fingerprint image according to the corrected fingerprint image data, and when the finger touches the capacitive sensor corresponding to the bad point, the corrected fingerprint image data is given. Thereby, the detection and correction of the dead pixels on the fingerprint module during the fingerprint recognition process are realized, and the training of the bad point data is performed, thereby further improving the fingerprint image quality and the fingerprint recognition rate.
- the present application also proposes a fingerprint image processing apparatus.
- FIG. 7 is a schematic structural diagram of a fingerprint image processing apparatus according to an embodiment of the present application.
- the fingerprint image processing apparatus includes:
- the generating module 11 is configured to generate, by the capacitive sensor, fingerprint image data corresponding to the contact finger when the fingerprint is entered;
- the identification module 12 is configured to mark fingerprint image data that does not belong to the preset data range as a bad point;
- a correction module 13 configured to correct fingerprint image data of the dead point according to the data range
- the processing module 14 is configured to generate a corresponding fingerprint image according to the corrected fingerprint image data.
- correction module 13 is specifically configured to:
- the fingerprint image data larger than the data range is reduced, so that the subtracted fingerprint image data belongs to the data range.
- correction module 13 is specifically configured to:
- the fingerprint image data smaller than the data range is compensated, so that the compensated fingerprint image data belongs to the data range.
- correction module 13 is specifically configured to:
- the fingerprint image data of the dead pixels is updated by applying the average value of the fingerprint image data belonging to the data range.
- the fingerprint image processing apparatus of the embodiment of the present application generates and contacts a finger through a capacitive sensor when the fingerprint is recorded.
- Corresponding fingerprint image data marking fingerprint image data that does not belong to the preset data range is a bad point, correcting the fingerprint image data of the bad point according to the data range, and generating a corresponding fingerprint image according to the corrected fingerprint image data.
- FIG. 8 is a schematic structural diagram of a fingerprint image processing apparatus according to another embodiment of the present application.
- the fingerprint image processing apparatus further includes:
- the obtaining module 15 is configured to obtain an average value of the fingerprint image sample data, and obtain a difference between the finger valley peaks in the fingerprint image sample data;
- a setting module 16 is provided for setting the data range based on the average value and the difference value.
- the correction module 13 is further configured to store the corrected fingerprint image data of the dead pixel, and when the finger touches the capacitance sensor corresponding to the bad point, the corrected fingerprint image data is given.
- the fingerprint image processing apparatus of the embodiment of the present application first acquires a difference between an average value of the fingerprint image sample data and a finger valley peak, and sets the data range according to the average value and the difference value, and when the fingerprint is entered,
- the capacitive sensor generates fingerprint image data corresponding to the contact finger, marks the fingerprint image data that does not belong to the preset data range as a bad point, applies an average value of the fingerprint image data belonging to the data range, and updates the fingerprint image data of the bad point.
- the detection and correction of the dead pixels on the fingerprint module during the fingerprint recognition process are realized, and the training of the bad point data is performed, thereby further improving the fingerprint image quality and the fingerprint recognition rate.
- the present application also proposes a terminal device.
- the terminal device provided in this embodiment includes: a fingerprint module having a capacitive sensor, and a fingerprint image processing device, wherein the fingerprint image processing device can adopt the fingerprint image processing device provided by the above embodiment of the present invention, and the fingerprint module with the capacitive sensor
- a fingerprint module having a capacitive sensor according to the above embodiment of the present invention may be employed.
- the terminal device has many types, and may include, for example, a mobile phone, an attendance machine, a payment device, or an access control device.
- the terminal device of the embodiment of the present invention generates fingerprint image data corresponding to the contact finger through the capacitive sensor when the fingerprint is recorded by the fingerprint image processing device; and marks the fingerprint image data that does not belong to the preset data range as a bad point; according to the data Correcting the fingerprint image data of the dead point; generating a corresponding finger according to the corrected fingerprint image data Grain image.
- the present application also proposes another terminal device.
- the terminal device provided in this embodiment, as shown in FIG. 9, includes a housing 91, a processor 92, a memory 93, a circuit board 94, and a power supply circuit 95, wherein the circuit board 94 is disposed inside the space enclosed by the housing 91.
- the processor 92 and the memory 93 are disposed on the circuit board 94; the power supply circuit 95 is for supplying power to the respective circuits or devices of the mobile terminal; the memory 93 is for storing executable program code; and the processor 92 is stored by reading the memory 93. Executable code to run a program corresponding to the executable code for performing the following steps:
- the fingerprint image data corresponding to the contact finger is generated by the capacitance sensor
- a corresponding fingerprint image is generated according to the corrected fingerprint image data.
- the terminal device of the embodiment of the present application reads a program corresponding to the executable program code by using a processor to read executable program code stored in the memory, and is configured to perform the following steps: when the fingerprint is entered, the capacitive sensor generates and generates Touching the fingerprint image data corresponding to the finger; marking the fingerprint image data that does not belong to the preset data range as a bad point; correcting the fingerprint image data of the bad point according to the data range; generating a corresponding fingerprint image according to the corrected fingerprint image data .
- the recognition and correction of the dead pixels on the fingerprint module during the fingerprint recognition process are realized, and the fingerprint image quality and the fingerprint recognition rate are improved.
- the present invention also provides a non-volatile computer storage medium storing one or more programs, when the one or more programs are executed by a device, causing the The device performs the fingerprint image processing method of the first aspect of the present invention.
- first and second are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated.
- features defining “first” or “second” may include at least one of the features, either explicitly or implicitly.
- the meaning of "a plurality” is two or more unless specifically and specifically defined otherwise.
- a "computer-readable medium” can be any apparatus that can contain, store, communicate, propagate, or transport a program for use in an instruction execution system, apparatus, or device, or in conjunction with the instruction execution system, apparatus, or device.
- computer readable media include the following: electrical connections (electronic devices) having one or more wires, portable computer disk cartridges (magnetic devices), random access memory (RAM), Read only memory (ROM), erasable editable read only memory (EPROM or flash memory), fiber optic devices, and portable compact disk read only memory (CDROM).
- the computer readable medium may even be a paper or other suitable medium on which the program can be printed, as it may be optically scanned, for example by paper or other medium, followed by editing, interpretation or, if appropriate, other suitable The method is processed to obtain the program electronically and then stored in computer memory.
- portions of the invention may be implemented in hardware, software, firmware or a combination thereof.
- multiple steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system.
- a suitable instruction execution system For example, if implemented in hardware, as in another embodiment, it can be implemented by any one or combination of the following techniques well known in the art: having logic gates for implementing logic functions on data signals. Discrete logic circuits, application specific integrated circuits with suitable combinational logic gates, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.
- each functional unit in each embodiment of the present invention may be integrated into one processing module, or may be each Units exist physically separately, or two or more units can be integrated into one module.
- the above integrated modules can be implemented in the form of hardware or in the form of software functional modules.
- the integrated modules, if implemented in the form of software functional modules and sold or used as stand-alone products, may also be stored in a computer readable storage medium.
- the above mentioned storage medium may be a read only memory, a magnetic disk or an optical disk or the like.
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Abstract
本申请提出一种指纹图像处理方法、装置和终端设备，其中，该方法包括：指纹录入时，通过电容传感器生成与接触手指对应的指纹图像数据；标记不属于预设数据范围的指纹图像数据为坏点；根据数据范围修正坏点的指纹图像数据；根据修正后的指纹图像数据生成对应的指纹图像。通过本申请提供的指纹图像处理方法、装置和终端设备，实现了指纹识别过程中对指纹模组上坏点的识别和修正，提高了指纹图像质量和指纹识别率。
Description
相关申请的交叉引用
本申请要求广东欧珀移动通信有限公司于2015年11月13日提交的、发明名称为“指纹图像处理方法、装置和终端设备”的、中国专利申请号“201510786430.5”的优先权。
本申请涉及指纹识别技术领域，尤其涉及一种指纹图像处理方法、装置和终端设备。
随着指纹识别技术的发展，越来越多的终端设备集成指纹模组的指纹识别功能，由于指纹模组中使用的栅格阵列封装LGA厚度、材料，涂层厚度以及生产工艺方面的不同，各方面工艺的误差，指纹模组无法完全达到一个十分理想的情况，或多或少会出现一些坏点。
目前，根据坏点个数对模组质量进行管控，如果坏点个数超过预设阈值，该产品不能出货；同时坏点的另外一个管控参数是任何单位区域内的坏点个数不能超过阈值，这样的管控范围是防止坏点过于集中，过于集中会导致图像某一个区域整体全黑或者全白，无法识别。但是即使这样管控，用户手里的产品指纹模组的坏点始终存在。
由于坏点存在，对生成的指纹图像会产生影响，例如：本来是连接的一条线会因为坏点而中断，或者本来是白色区域，因为多了个坏点造成误识别，甚至有时候把会坏机当成特征点，图1为包含坏点的指纹图像示意图。由此可见，坏点会造成指纹图像质量变差，降低指纹的识别率。
发明内容
本发明旨在至少在一定程度上解决相关技术中的技术问题之一。为此，本申请的第一个目的在于提出一种指纹图像处理方法，该方法实现了指纹识别过程中对指纹模组上坏点的识别和修正，提高了指纹图像质量和指纹识别率。
本发明的第二个目的在于提出一种指纹图像处理装置。
本发明的第三个目的在于提出一种终端设备。
本申请的第四个目的在于提出一种终端设备。
本发明的第五个目的在于提出一种非易失性计算机存储介质。
为达上述目的，本申请第一方面实施例提出了一种指纹图像处理方法，包括：指纹录入时，通过电容传感器生成与接触手指对应的指纹图像数据；标记不属于预设数据范围的指纹图像数据为坏点；根据所述数据范围修正所述坏点的指纹图像数据；根据修正后的指纹图像数据生成对应的指纹图像。
为达上述目的，本申请第二方面实施例提出了一种指纹图像处理装置，包括：生成模块，用于指纹录入时，通过电容传感器生成与接触手指对应的指纹图像数据；识别模块，用于标记不属于预设数据范围的指纹图像数据为坏点；修正模块，用于根据所述数据范围修正所述坏点的指纹图像数据；处理模块，用于根据修正后的指纹图像数据生成对应的指纹图像。
为达上述目的，本申请第三方面实施例提出了一种终端设备，包括：具有电容传感器的指纹模组，以及如上所述的指纹图像处理装置。
为达上述目的，本申请第四方面实施例提出了一种终端设备，包括：壳体、处理器、存储器、电路板和电源电路，其中，所述电路板安置在所述壳体围成的空间内部，所述处理器和所述存储器设置在所述电路板上；所述电源电路，用于为所述移动终端的各个电路或器件供电；所述存储器用于存储可执行程序代码；所述处理器通过读取所述存储器中存储的可执行程序代码来运行与所述可执行程序代码对应的程序，以用于执行以下步骤：指纹录入时，通过电容传感器生成与接触手指对应的指纹图像数据；标记不属于预设数据范围的指纹图像数据为坏点；根据所述数据范围修正所述坏点的指纹图像数据；根据修正后的指纹图像数据生成对应的指纹图像。
本发明第五方面实施例提供了一种非易失性计算机存储介质，所述计算机存储介质存储有一个或者多个程序，当所述一个或者多个程序被一个设备执行时，使得所述设备执行以本发明第一方面实施例的指纹图像处理方法。
本发明实现了指纹识别过程中对指纹模组上坏点的识别和修正，提高了指纹图像质量和指纹识别率。
为了更清楚地说明本发明实施例中的技术方案，下面将对实施例中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1为包含坏点的指纹图像示意图；
图2是本申请一个实施例的指纹图像处理方法的流程图；
图3为对指纹图像数据仿真形成的具有指峰指谷的三维图形；
图4为指纹图像数据示意图；
图5为指纹图像示意图；
图6是本申请另一个实施例的指纹图像处理方法的流程图；
图7是本申请一个实施例的指纹图像处理装置的结构示意图；
图8是本申请另一个实施例的指纹图像处理装置的结构示意图；
图9是本申请一个实施例的终端设备的结构示意图。
下面详细描述本申请的实施例，所述实施例的示例在附图中示出，其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施例是示例性的，旨在用于解释本申请，而不能理解为对本申请的限制。
下面参考附图描述本申请实施例的指纹图像处理方法、装置和终端设备。
图2是本申请一个实施例的指纹图像处理方法的流程图。
如图2所示，该指纹图像处理方法包括：
步骤101，指纹录入时，通过电容传感器生成与接触手指对应的指纹图像数据。
具体地，本实施例提供的指纹图像处理方法被配置在支持指纹模组进行指纹识别的终端设备中为例进行说明。需要注意的是，终端设备的类型很多，可以根据应用需要进行选择，例如：手机、考勤机、支付设备、或，门禁控制设备等。
当用户通过指纹模组录入指纹时，通过指纹模组中预设的电容传感器阵列生成与接触手指对应的指纹图像数据。由于人的手指指纹上有凹凸不平的指谷和指峰，因此，电容传感器根据指谷和指峰与电容传感器形成的电容值大小不同，来判断指谷和指峰的具体分布。具体的工作原理是：通过对每个像素点上的电容传感器预先充电到参考电压，当手指接触到电容传感器，由于指峰是凸起，指谷是凹下，因此，指峰和指谷到电容传感器平面的距离不同。根据电容值与距离的关系，会在指峰和指谷的位置形成不同的电容值。然后利用放电电流进行放电，由于指峰和指谷对应的电容值不同，所以对应的放电速度也不同。指峰离电容传感器近，电容量高，放电较慢，指谷离电容传感器远，电容量低，放电较快。根据放电率的不同，可以确定指峰和指谷的位置，从而生成与接触手指对应的指纹图像数
据。
步骤102，标记不属于预设数据范围的指纹图像数据为坏点。
具体地，虽然正常管控范围内的坏点并不会造成整个指纹模组的失效，但是，会影响指纹图像的质量(参见图1)。指纹模组上坏点的产生因素很多，比如芯片像素点出现坏点，即不论手指如何移动该点图像不变；或者，表面划伤，会出现一连串的坏点；或者，指纹模组盖板和芯片贴合的时候胶水出现气泡，气泡内是空气其介电常数要远远小于盖板的介常数，这会导致在该点图像出现明显的白点；或者，杂质和异物夹杂在指纹模组中，由于杂质的介电常数和盖板的无法统一比较，有的高有的低，便会出现有的呈现黑色有的呈现白色。但是，坏点具有固定性，即坏点在指纹图像上的位置是固定不变的，坏点的从图像上分析表现为明显位置不变的白点或黑点。
虽然手指指纹有指峰和指谷的凹凸不平，但是通过电容传感器生成与接触手指对应的指纹图像数据相差不大，即便指峰和指谷之间的差值也在有限范围内。基于坏点的固定性和指纹图像数据的相似性，可以通过分析指纹图像数据来识别坏点。
图3为对指纹图像数据仿真形成的具有指峰指谷的三维图形。参见图3，可以看出与接触手指对应的每个指纹图像数据形成一个三维图，在每一个截面上，数据是相差无几的，但是会有一些点异常的高或者异常的低。由此可见，与坏点对应的指纹图像数据都是远远超出预设上限和下限的范围值。打比方来说，一个湖面虽然有波纹，但是都在正常范围内，如果出现漩涡或者激起很高的浪花该处就是坏点。图4为指纹图像数据示意图。参见图4，每个平行线上，因为布局走线的关系，相邻的数据很接近，但是该条线上出现某些点数值很高或者很低就是坏点。
基于上述原理，根据预设的数据范围检测指纹图像数据，标记不属于预设数据范围的指纹图像数据为坏点。其中，预设的数据范围可以根据指纹图像数据的历史样本集进行确定，也可以根据实际应用情况进行调整，本实施例对此不作限制。
步骤103，根据数据范围修正所述坏点的指纹图像数据。
具体地，根据预设数据范围从指纹图像数据中识别出坏点后，根据该数据范围修正坏点的指纹图像数据，使修正后的指纹图像数据属于预设的数据范围。需要注意的是，对坏点的指纹图像数据进行修正方式很多，可以根据实际应用需要进行选择，具体说明如下：
消减大于预设数据范围的指纹图像数据，使消减后的指纹图像数据属于该数据范围，或者，
补偿小于预设数据范围的指纹图像数据，使补偿后的指纹图像数据属于该数据范围，或者，
应用属于所述数据范围的指纹图像数据的平均值，更新所述坏点的指纹图像数据。
步骤104，根据修正后的指纹图像数据生成对应的指纹图像。
具体地，根据预设的数据范围对坏点的指纹图像数据进行修正后，所有的指纹图像数据都属于预设的数据范围，进而根据修正后的指纹图像数据在与各个电容传感器对应的像素点上生成对应的指纹图像。
图5为指纹图像示意图，参见图5，图5的左侧图为根据与指纹模组接触的手指的原始指纹图像数据生成的指纹图像，由左侧图可见，基于上述分析，箭头所指的地方的指纹图像数据超出预设的数据范围，即为坏点，表现为白点，根据预设的数据范围对该处指纹图像数据进行修正，根据修正后的指纹图像数据生成的指纹图像，如图5的右侧图所示，表现的效果便是该处白点坏点会变成和周围一样的均值，成黑点，而自然形成一条线，也就是指峰，使得之前坏点处生成的断点指纹图像得以修复，正常显示。
本实施例的指纹图像处理方法，指纹录入时，通过电容传感器生成与接触手指对应的指纹图像数据，标记不属于预设数据范围的指纹图像数据为坏点，根据所述数据范围修正所述坏点的指纹图像数据，根据修正后的指纹图像数据生成对应的指纹图像。由此，实现了指纹识别过程中对指纹模组上坏点的检测和补偿，提高了指纹图像质量和指纹识别率。
图6是本申请另一个实施例的指纹图像处理方法的流程图。
如图6所示，该指纹图像处理方法包括：
步骤201，获取指纹图像样本数据的平均值和指谷指峰的差值，根据所述平均值和所述差值设置所述数据范围。
步骤202，指纹录入时，通过电容传感器生成与接触手指对应的指纹图像数据；
步骤203，标记不属于预设数据范围的指纹图像数据为坏点；
步骤204，应用属于所述数据范围的指纹图像数据的平均值，更新所述坏点的指纹图像数据，并存储所述坏点的修正指纹图像数据；
步骤205，根据修正后的指纹图像数据生成对应的指纹图像。
步骤206，当手指接触到与所述坏点对应的电容传感器时，赋予所述修正指纹图像数据。
具体地，根据获取的指纹图像样本数据确定预设的数据范围，首先获取指纹图像样本数据的平均值和指谷指峰的差值，然后根据该平均值和差值设置数据范围。举例说明如下：
假设指纹图像样本数据的均值为1300，而指峰与指谷之间的差值也在300以内，也就是正常的底层数据在1000—1600之间，因此设置数据范围的最高上限为2000，最低下限为500。
指纹录入时，通过电容传感器生成与接触手指对应的指纹图像数据，然后根据预设的数据范围检测指纹图像数据，标记不属于预设数据范围的指纹图像数据为坏点，当超出最高上下限时，便判定与该点数据的位置为坏点。
应用属于数据范围的指纹图像数据的平均值，更新坏点的指纹图像数据，并存储坏点的修正指纹图像数据，然后根据修正后的指纹图像数据生成对应的指纹图像。
在用户后续不断使用的过程中，当手指接触到与所述坏点对应的电容传感器时，对该处坏点的底层数据值不予采用于图像生成，而是直接赋予预先存储的与坏点对应的修正指纹图像数据，进而生成指纹图像。
本实施例的指纹图像处理方法，首先获取指纹图像样本数据的平均值和指谷指峰的差值，根据所述平均值和所述差值设置所述数据范围，当指纹录入时，通过电容传感器生成与接触手指对应的指纹图像数据，标记不属于预设数据范围的指纹图像数据为坏点，应用属于所述数据范围的指纹图像数据的平均值，更新所述坏点的指纹图像数据并存储，根据修正后的指纹图像数据生成对应的指纹图像，当手指接触到与所述坏点对应的电容传感器时，赋予所述修正指纹图像数据。由此，实现了指纹识别过程中对指纹模组上坏点的检测和修正，并且对坏点数据进行训练学习，进一步地提高了指纹图像质量和指纹识别率。
为了实现上述实施例，本申请还提出一种指纹图像处理装置。
图7是本申请一个实施例的指纹图像处理装置的结构示意图。
如图7所示，该指纹图像处理装置包括：
生成模块11，用于指纹录入时，通过电容传感器生成与接触手指对应的指纹图像数据；
识别模块12，用于标记不属于预设数据范围的指纹图像数据为坏点；
修正模块13，用于根据所述数据范围修正所述坏点的指纹图像数据；
处理模块14，用于根据修正后的指纹图像数据生成对应的指纹图像。
在一个实施例中，修正模块13，具体用于：
消减大于数据范围的指纹图像数据，使消减后的指纹图像数据属于数据范围。
在另一个实施例中，修正模块13，具体用于：
补偿小于数据范围的指纹图像数据，使补偿后的指纹图像数据属于数据范围。
在另一个实施例中，修正模块13，具体用于：
应用属于数据范围的指纹图像数据的平均值，更新坏点的指纹图像数据。
需要说明的是，前述对指纹图像处理方法实施例的解释说明也适用于该实施例的指纹图像处理装置，此处不再赘述。
本申请实施例的指纹图像处理装置，在指纹录入时，通过电容传感器生成与接触手指
对应的指纹图像数据，标记不属于预设数据范围的指纹图像数据为坏点，根据所述数据范围修正所述坏点的指纹图像数据，根据修正后的指纹图像数据生成对应的指纹图像。由此，实现了指纹识别过程中对指纹模组上坏点的检测和补偿，提高了指纹图像质量和指纹识别率。
图8是本申请另一个实施例的指纹图像处理装置的结构示意图。
如图8所示，基于图7所示实施例，该指纹图像处理装置还包括：
获取模块15，用于获取指纹图像样本数据的平均值，并获取指纹图像样本数据中指谷指峰的差值；
设置模块16，用于根据平均值和差值设置所述数据范围。
修正模块13，还用于存储坏点的修正指纹图像数据，当手指接触到与坏点对应的电容传感器时，赋予修正指纹图像数据。
需要说明的是，前述对指纹图像处理方法实施例的解释说明也适用于该实施例的指纹图像处理装置，此处不再赘述。
本申请实施例的指纹图像处理装置，首先获取指纹图像样本数据的平均值和指谷指峰的差值，根据所述平均值和所述差值设置所述数据范围，当指纹录入时，通过电容传感器生成与接触手指对应的指纹图像数据，标记不属于预设数据范围的指纹图像数据为坏点，应用属于所述数据范围的指纹图像数据的平均值，更新所述坏点的指纹图像数据并存储，根据修正后的指纹图像数据生成对应的指纹图像，当手指接触到与所述坏点对应的电容传感器时，赋予所述修正指纹图像数据。由此，实现了指纹识别过程中对指纹模组上坏点的检测和修正，并且对坏点数据进行训练学习，进一步地提高了指纹图像质量和指纹识别率。
为了实现上述实施例，本申请还提出一种终端设备
本实施例提供的终端设备包括：具有电容传感器的指纹模组，以及指纹图像处理装置，其中，指纹图像处理装置可以采用本发明上述实施例提供的指纹图像处理装置，具有电容传感器的指纹模组可以采用本发明上述实施例涉及的具有电容传感器的指纹模组。
需要说明的是，终端设备的类型很多，例如可以包括：手机、考勤机、支付设备、或，门禁控制设备。
需要说明的是，前述对指纹图像处理方法实施例的解释说明也适用于该实施例的终端设备，其实现原理类似，此处不再赘述。
本申请实施例的终端设备，通过指纹图像处理装置在指纹录入时，通过电容传感器生成与接触手指对应的指纹图像数据；标记不属于预设数据范围的指纹图像数据为坏点；根据所述数据范围修正所述坏点的指纹图像数据；根据修正后的指纹图像数据生成对应的指
纹图像。由此，实现了指纹识别过程中对指纹模组上坏点的识别和修正，提高了指纹图像质量和指纹识别率。
为了实现上述实施例，本申请还提出另一种终端设备。
本实施例提供的终端设备，如图9所示，包括：壳体91、处理器92、存储器93、电路板94和电源电路95，其中，电路板94安置在壳体91围成的空间内部，处理器92和存储器93设置在电路板94上；电源电路95，用于为移动终端的各个电路或器件供电；存储器93用于存储可执行程序代码；处理器92通过读取存储器中93存储的可执行程序代码来运行与可执行程序代码对应的程序，以用于执行以下步骤：
指纹录入时，通过电容传感器生成与接触手指对应的指纹图像数据；
标记不属于预设数据范围的指纹图像数据为坏点；
根据所述数据范围修正所述坏点的指纹图像数据；
根据修正后的指纹图像数据生成对应的指纹图像。
需要说明的是，前述对指纹图像处理方法实施例的解释说明也适用于该实施例的终端设备，其实现原理类似，此处不再赘述。
本申请实施例的终端设备，通过处理器读取存储器中存储的可执行程序代码来运行与所述可执行程序代码对应的程序，以用于执行以下步骤：指纹录入时，通过电容传感器生成与接触手指对应的指纹图像数据；标记不属于预设数据范围的指纹图像数据为坏点；根据所述数据范围修正所述坏点的指纹图像数据；根据修正后的指纹图像数据生成对应的指纹图像。由此，实现了指纹识别过程中对指纹模组上坏点的识别和修正，提高了指纹图像质量和指纹识别率。
为了实现上述实施例，本发明还提出一种非易失性计算机存储介质，所述计算机存储介质存储有一个或者多个程序，当所述一个或者多个程序被一个设备执行时，使得所述设备执行以本发明第一方面实施例的指纹图像处理方法。
在本说明书的描述中，参考术语“一个实施例”、“一些实施例”、“示例”、“具体示例”、或“一些示例”等的描述意指结合该实施例或示例描述的具体特征、结构、材料或者特点包含于本发明的至少一个实施例或示例中。在本说明书中，对上述术语的示意性表述不必须针对的是相同的实施例或示例。而且，描述的具体特征、结构、材料或者特点可以在任一个或多个实施例或示例中以合适的方式结合。此外，在不相互矛盾的情况下，本领域的技术人员可以将本说明书中描述的不同实施例或示例以及不同实施例或示例的特征进行结合和组合。
此外，术语“第一”、“第二”仅用于描述目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有“第一”、“第二”的特征可以明示或者隐含地包括至少一个该特征。在本发明的描述中，“多个”的含义是两个或两个以上，除非另有明确具体的限定。
流程图中或在此以其他方式描述的任何过程或方法描述可以被理解为，表示包括一个或更多个用于实现特定逻辑功能或过程的步骤的可执行指令的代码的模块、片段或部分，并且本发明的优选实施方式的范围包括另外的实现，其中可以不按所示出或讨论的顺序，包括根据所涉及的功能按基本同时的方式或按相反的顺序，来执行功能，这应被本发明的实施例所属技术领域的技术人员所理解。
在流程图中表示或在此以其他方式描述的逻辑和/或步骤，例如，可以被认为是用于实现逻辑功能的可执行指令的定序列表，可以具体实现在任何计算机可读介质中，以供指令执行系统、装置或设备(如基于计算机的系统、包括处理器的系统或其他可以从指令执行系统、装置或设备取指令并执行指令的系统)使用，或结合这些指令执行系统、装置或设备而使用。就本说明书而言，"计算机可读介质"可以是任何可以包含、存储、通信、传播或传输程序以供指令执行系统、装置或设备或结合这些指令执行系统、装置或设备而使用的装置。计算机可读介质的更具体的示例(非穷尽性列表)包括以下：具有一个或多个布线的电连接部(电子装置)，便携式计算机盘盒(磁装置)，随机存取存储器(RAM)，只读存储器(ROM)，可擦除可编辑只读存储器(EPROM或闪速存储器)，光纤装置，以及便携式光盘只读存储器(CDROM)。另外，计算机可读介质甚至可以是可在其上打印所述程序的纸或其他合适的介质，因为可以例如通过对纸或其他介质进行光学扫描，接着进行编辑、解译或必要时以其他合适方式进行处理来以电子方式获得所述程序，然后将其存储在计算机存储器中。
应当理解，本发明的各部分可以用硬件、软件、固件或它们的组合来实现。在上述实施方式中，多个步骤或方法可以用存储在存储器中且由合适的指令执行系统执行的软件或固件来实现。例如，如果用硬件来实现，和在另一实施方式中一样，可用本领域公知的下列技术中的任一项或他们的组合来实现：具有用于对数据信号实现逻辑功能的逻辑门电路的离散逻辑电路，具有合适的组合逻辑门电路的专用集成电路，可编程门阵列(PGA)，现场可编程门阵列(FPGA)等。
本技术领域的普通技术人员可以理解实现上述实施例方法携带的全部或部分步骤是可以通过程序来指令相关的硬件完成，所述的程序可以存储于一种计算机可读存储介质中，该程序在执行时，包括方法实施例的步骤之一或其组合。
此外，在本发明各个实施例中的各功能单元可以集成在一个处理模块中，也可以是各
个单元单独物理存在，也可以两个或两个以上单元集成在一个模块中。上述集成的模块既可以采用硬件的形式实现，也可以采用软件功能模块的形式实现。所述集成的模块如果以软件功能模块的形式实现并作为独立的产品销售或使用时，也可以存储在一个计算机可读取存储介质中。
上述提到的存储介质可以是只读存储器，磁盘或光盘等。尽管上面已经示出和描述了本发明的实施例，可以理解的是，上述实施例是示例性的，不能理解为对本发明的限制，本领域的普通技术人员在本发明的范围内可以对上述实施例进行变化、修改、替换和变型。
Claims (16)
- 一种指纹图像处理方法，其特征在于，包括以下步骤：指纹录入时，通过电容传感器生成与接触手指对应的指纹图像数据；标记不属于预设数据范围的指纹图像数据为坏点；根据所述数据范围修正所述坏点的指纹图像数据；根据修正后的指纹图像数据生成对应的指纹图像。
- 如权利要求1所述的方法，其特征在于，所述根据所述数据范围修正所述坏点的指纹图像数据，包括：消减大于所述数据范围的指纹图像数据，使消减后的指纹图像数据属于所述数据范围。
- 如权利要求1所述的方法，其特征在于，所述根据所述数据范围修正所述坏点的指纹图像数据，包括：补偿小于所述数据范围的指纹图像数据，使补偿后的指纹图像数据属于所述数据范围。
- 如权利要求1所述的方法，其特征在于，所述根据所述数据范围修正所述坏点的指纹图像数据，包括：应用属于所述数据范围的指纹图像数据的平均值，更新所述坏点的指纹图像数据。
- 如权利要求1-4任一所述的方法，其特征在于，所述根据所述数据范围修正所述坏点的指纹图像数据之后，还包括：存储所述坏点的修正指纹图像数据；当手指接触到与所述坏点对应的电容传感器时，赋予所述修正指纹图像数据。
- 如权利要求1-4任一所述的方法，其特征在于，还包括：获取指纹图像样本数据的平均值；获取所述指纹图像样本数据中指谷指峰的差值；根据所述平均值和所述差值设置所述数据范围。
- 如权利要求1所述的方法，其特征在于，通过电容传感器生成与接触手指对应的指纹图像数据，包括：通过指纹模组中预设的电容传感器阵列生成与接触手指对应的指纹图像数据。
- 一种指纹图像处理装置，其特征在于，包括：生成模块，用于指纹录入时，通过电容传感器生成与接触手指对应的指纹图像数据；识别模块，用于标记不属于预设数据范围的指纹图像数据为坏点；修正模块，用于根据所述数据范围修正所述坏点的指纹图像数据；处理模块，用于根据修正后的指纹图像数据生成对应的指纹图像。
- 如权利要求8所述的装置，其特征在于，所述修正模块，具体用于：消减大于所述数据范围的指纹图像数据，使消减后的指纹图像数据属于所述数据范围。
- 如权利要求8所述的装置，其特征在于，所述修正模块，具体用于：补偿小于所述数据范围的指纹图像数据，使补偿后的指纹图像数据属于所述数据范围。
- 如权利要求8所述的装置，其特征在于，所述修正模块，具体用于：应用属于所述数据范围的指纹图像数据的平均值，更新所述坏点的指纹图像数据。
- 如权利要求8-11任一所述的装置，其特征在于，还包括：存储模块，用于存储所述坏点的修正指纹图像数据；所述修正模块，还用于当手指接触到与所述坏点对应的电容传感器时，赋予所述修正指纹图像数据。
- 如权利要求8-11任一所述的装置，其特征在于，还包括：获取模块，用于获取指纹图像样本数据的平均值，并获取所述指纹图像样本数据中指谷指峰的差值；设置模块，用于根据所述平均值和所述差值设置所述数据范围。
- 如权利要求8所述的装置，其特征在于，所述生成模块，用于：通过指纹模组中预设的电容传感器阵列生成与接触手指对应的指纹图像数据。
- 一种终端设备，其特征在于，包括：壳体、处理器、存储器、电路板和电源电路，其中，所述电路板安置在所述壳体围成的空间内部，所述处理器和所述存储器设置在所述电路板上；所述电源电路，用于为所述移动终端的各个电路或器件供电；所述存储器用于存储可执行程序代码；所述处理器通过读取所述存储器中存储的可执行程序代码来运行与所述可执行程序代码对应的程序，以用于执行以下步骤：指纹录入时，通过电容传感器生成与接触手指对应的指纹图像数据；标记不属于预设数据范围的指纹图像数据为坏点；根据所述数据范围修正所述坏点的指纹图像数据；根据修正后的指纹图像数据生成对应的指纹图像。
- 一种非易失性计算机存储介质，所述计算机存储介质存储有一个或者多个程序，当所述一个或者多个程序被一个设备执行时，使得所述设备执行权利要求1-7任一项所述的指纹图像处理方法。
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| CN106066685B (zh) * | 2016-05-30 | 2018-01-19 | 广东欧珀移动通信有限公司 | 一种解锁控制方法及终端设备 |
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| CN106228123B (zh) * | 2016-07-14 | 2019-02-12 | 浙江赢视科技有限公司 | 自动调整处理的指纹识别器及其识别方法 |
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| CN108665409B (zh) * | 2017-03-31 | 2021-10-26 | 奇景光电股份有限公司 | 指纹图像的合并方法与电子装置 |
| WO2019041243A1 (zh) * | 2017-08-31 | 2019-03-07 | 华为技术有限公司 | 指纹传感器功能的验证方法及终端 |
| CN107644220B (zh) * | 2017-09-30 | 2021-03-05 | 上海摩软通讯技术有限公司 | 移动终端的指纹识别方法及系统 |
| CN107729884A (zh) * | 2017-11-22 | 2018-02-23 | 广东欧珀移动通信有限公司 | 指纹识别方法、移动终端以及计算机可读存储介质 |
| CN208766682U (zh) * | 2018-09-30 | 2019-04-19 | 算丰科技（北京）有限公司 | 图形处理设备 |
| CN111353332B (zh) * | 2018-12-21 | 2023-06-02 | 中国电信股份有限公司 | 指纹图像处理方法、装置和计算机可读存储介质 |
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