WO2020237870A1 - 手部纹理信息的录入和验证方法、及录入和验证装置 - Google Patents

手部纹理信息的录入和验证方法、及录入和验证装置 Download PDF

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Publication number
WO2020237870A1
WO2020237870A1 PCT/CN2019/102990 CN2019102990W WO2020237870A1 WO 2020237870 A1 WO2020237870 A1 WO 2020237870A1 CN 2019102990 W CN2019102990 W CN 2019102990W WO 2020237870 A1 WO2020237870 A1 WO 2020237870A1
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Prior art keywords
image
hand
user
texture information
preset
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PCT/CN2019/102990
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English (en)
French (fr)
Inventor
沙内瓦拉瑞迪•耶姆
朱虹
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上海箩箕技术有限公司
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Publication of WO2020237870A1 publication Critical patent/WO2020237870A1/zh

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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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
    • G06F21/31—User authentication
    • G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
    • 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
    • G06V40/1365—Matching; Classification

Definitions

  • the present invention relates to the technical field of biometric identification, in particular to an input method and verification method, input device and verification device of hand texture information.
  • Fingerprint entry is to collect and store the user's fingerprints in advance.
  • the currently entered fingerprints are compared with the pre-stored fingerprints to verify the user's identity.
  • the current fingerprint entry technology usually requires multiple contacts between the user's finger and the entry interface to complete the entry of fingerprint data, and the efficiency of fingerprint entry is low.
  • the amount of characteristic information contained in a single fingerprint data is limited, the device is still unlocked by mistake, and the user's identity authentication has security risks.
  • the embodiment of the present invention provides a method for inputting hand texture information, including: collecting a user's hand image, the user's hand image including the user's finger texture information and palm texture information; the user's hand to be collected A part of the image is divided into a plurality of image regions, a plurality of image regions meeting preset input conditions are selected from the plurality of image regions, and feature information of the plurality of image regions is extracted; and the feature information of the plurality of image regions is stored For several hand texture feature templates.
  • selecting several image areas satisfying preset entry conditions from the multiple image areas includes: determining the image quality and/or image area of each image area in the multiple image areas; Select several image areas whose image quality meets the preset image quality standard and/or the image area meets the preset image area standard from the image areas.
  • determining the image quality of each of the plurality of image areas includes: using at least one image quality evaluation index to evaluate the image quality of each of the plurality of image areas to obtain each Quality evaluation values of image areas; selecting from the plurality of image areas a number of image areas whose image quality meets a preset image quality standard includes: selecting from the plurality of image areas the quality evaluation value is greater than a preset quality threshold Several image areas.
  • the image area is the area of finger texture information or palm texture information contained in each image area
  • selecting several image areas whose image area meets a preset image area standard from the multiple image areas includes: Select several image areas with an image area greater than a preset area threshold or an image area ratio greater than a preset area ratio threshold from the plurality of image areas.
  • collecting the user's hand image includes: when it is detected that the user touches or presses the hand texture information recognition module, controlling the hand texture information recognition module to collect the user's hand image.
  • collecting an image of the user's hand further includes: controlling the hand texture information recognition module to complete the processing of the hand texture information recognition module during the user's single touch or single pressing of the hand texture information recognition module. Collection of internal images.
  • dividing the collected user's hand image into multiple image regions includes: dividing the collected user's hand image into multiple image regions according to a sample size required by a preset hand texture information verification algorithm.
  • the input method further includes: prompting the user with a preset mark to place at least part of the finger and at least part of the palm in the preset collection area.
  • the embodiment of the present invention also provides a method for verifying hand texture information, which includes: collecting a user's hand image, the user's hand image including the user's finger texture information and palm texture information; The hand image is divided into a plurality of image regions, and a plurality of image regions satisfying preset verification conditions are selected from the plurality of image regions as a plurality of samples to be identified; feature information of the plurality of samples to be identified is extracted, and the plurality of The degree of matching between the feature information of the sample to be recognized and the plurality of pre-stored hand texture feature templates; and the generation of the said according to the degree of matching between the feature information of the plurality of samples to be recognized and the plurality of pre-stored hand texture feature templates The verification result of the user's hand texture information.
  • selecting several image areas from the multiple image areas as several samples to be identified includes: determining the image quality and/or image area of each of the multiple image areas; In the image area, several image areas whose image quality meets the preset image quality standard and/or the image area meets the preset image area standard are selected as several samples to be identified.
  • determining the image quality of each of the plurality of image areas includes: using at least one image quality evaluation index to evaluate the image quality of each of the plurality of image areas to obtain each The quality evaluation value of each image area; selecting several image areas whose image quality meets the preset image quality standard in the multiple image areas as a number of samples to be identified includes: setting the quality evaluation value of the multiple image areas greater than the predetermined Several image regions with quality thresholds are selected as a number of samples to be identified.
  • the image area is the area of finger texture information or palm texture information contained in each image area, and several image areas in the multiple image areas whose image areas meet a preset image area standard are selected as several Recognizing the sample includes: selecting several image regions with an image area greater than a preset area threshold or an image area ratio greater than a preset area ratio threshold among the plurality of image areas as the plurality of samples to be identified.
  • collecting the user's hand image includes: when it is detected that the user touches or presses the hand texture information recognition module, controlling the hand texture information recognition module to collect the user's hand image.
  • collecting an image of the user's hand further includes: controlling the hand texture information recognition module to complete the processing of the hand texture information recognition module during the user's single touch or single pressing of the hand texture information recognition module. Collection of internal images.
  • the verification method before collecting the user's hand image, the verification method further includes: prompting the user to place the hand in the preset collection area with a preset mark.
  • dividing the collected user's hand image into multiple image regions includes: dividing the collected user's hand image into multiple image regions according to a sample size required by a preset hand texture information verification algorithm.
  • generating a verification result of hand texture information according to the degree of matching between the feature information of the plurality of samples to be identified and the plurality of prestored hand texture feature templates includes: if the plurality of samples to be identified has more than If the feature information of a predetermined number of samples to be identified matches the multiple pre-stored hand texture feature templates, it is determined that the hand texture information verification is passed; otherwise, it is determined that the hand texture information verification fails.
  • the verification method further includes: generating the plurality of pre-stored hand texture feature templates using the entry method of the embodiment of the present invention.
  • the size of each image area obtained by dividing the collected user's hand image in the verification method and the size of each image area obtained by dividing the collected user's hand image in the input method the same.
  • the embodiment of the present invention provides a hand texture information input device, which includes: an image acquisition module for collecting a user's hand image, the user's hand image including the user's finger texture information and palm texture information; A processing module, configured to divide the collected user's hand image into multiple image areas, select from the multiple image areas several image areas meeting preset input conditions, and extract feature information of the several image areas; And a storage module for storing the feature information of the several image areas as several hand texture feature templates.
  • the image acquisition module includes: a screen having a first surface suitable for contact with a user's hand and a second surface opposite to the first surface; and a sensor disposed on the screen On the second surface of the screen, the sensor is adapted to collect the user's hand image within the entire screen range.
  • An embodiment of the present invention provides a hand texture information verification device, which includes: an image acquisition module for collecting a user's hand image, the user's hand image including the user's finger texture information and palm texture information;
  • the processing module is used to divide the collected user's hand image into multiple image areas, select from the multiple image areas several image areas meeting preset verification conditions as several samples to be recognized, and extract the several samples to be recognized
  • the feature information of the sample and confirm the degree of matching between the feature information of the plurality of samples to be identified and the plurality of pre-stored hand texture feature templates, and according to the feature information of the plurality of samples to be identified and the plurality of pre-stored hands
  • the matching degree of the texture feature template generates a verification result of the user's hand texture information; and a storage module for storing the multiple hand texture feature templates.
  • the image acquisition module includes: a screen having a first surface suitable for contact with a user's hand and a second surface opposite to the first surface; and a sensor disposed on the screen On the second surface of the screen, the sensor is adapted to collect the user's hand image within the entire screen range.
  • the texture information of the entire hand can be collected By dividing the collected user’s hand image into multiple image areas, it is convenient to process the image data by partition; selecting from the multiple image areas a number of image areas that meet the preset entry conditions, and extracting the number of image areas Feature information reduces the number of image areas where feature information needs to be extracted, thereby reducing the amount of calculation; storing the feature information of the several image areas as several hand texture feature templates to facilitate the subsequent verification of hand texture information.
  • the hand texture feature is divided into regions for comparison; since the multiple image regions are obtained by spatially dividing the user's hand image, some of the hand texture feature templates may only include fingers Texture information. Some feature templates may only include palm texture information, and some feature templates may include both finger texture information and palm texture information. Therefore, the user’s hand texture features obtained by the input method of hand texture information are more To enrich and lay a foundation for correspondingly improving the verification efficiency and verification security of hand texture information.
  • collecting the image of the user's hand further includes: controlling the hand texture information recognition module to complete the identification of the user's hand during the single touch or single pressing of the hand texture information recognition module by the user.
  • Image collection because the hand texture information input method can collect the user's full hand image, a single touch or a single press of the user is sufficient to provide rich user hand texture data, compared to the need for a single finger
  • the hand texture information entry method of the embodiment of the present invention greatly saves the user's time for participating in entry and improves the user's hand texture information Input efficiency.
  • the texture information of the entire hand can be collected By dividing the collected user’s hand image into multiple image areas, it is convenient for subsequent partition processing of image data and partition verification feature information; from the multiple image areas, a number of image areas meeting preset verification conditions are selected as a number of waiting Identifying the samples, extracting the feature information of the plurality of samples to be identified, reduces the number of image regions where feature information needs to be extracted, thereby reducing the amount of calculation.
  • the verification method of the embodiment of the present invention performs the verification of samples to be identified that contain a variety of different texture information. Authentication, the security of user identification is significantly improved.
  • collecting an image of the user’s hand may also include: controlling the hand texture information recognition module to complete the recognition of the user’s hand during a single touch or single pressing of the hand texture information recognition module by the user. Collection of internal images. Compared with the prior art when single-finger operation is used for verification, since the contact area of the finger is limited, the user may need to press multiple times to authenticate successfully.
  • the verification method of the embodiment of the present invention the user touches with the whole hand. This method increases the probability that the user passes the verification with a single touch or a single press, that is, the verification efficiency is improved, and the user experience is improved.
  • generating a verification result of hand texture information according to the degree of matching between the feature information of the plurality of samples to be identified and the plurality of pre-stored hand texture feature templates may include: if the plurality of samples to be identified has more than If the feature information of the predetermined number of samples to be identified matches the multiple pre-stored hand texture feature templates, it is determined that the hand texture information verification has passed, otherwise it is determined that the hand texture information verification has failed, which is convenient for the user according to the actual situation.
  • the requirements of the security level in the application set the criteria for passing the verification. For example, if the security level for user verification is higher, the predetermined number can be set higher, otherwise, the predetermined number can be reduced.
  • the verification method in the embodiment of the present invention has high flexibility and is suitable for a variety of application scenarios.
  • the method for inputting and verifying hand texture information in the embodiment of the present invention can also solve the problem that users cannot perform fingerprint recognition due to the long-term wear of fingertip fingerprints, because the user can use texture information from other positions of the hand to complete the input and verification ,
  • the universality is enhanced.
  • FIG. 1 is a flowchart of a method 10 for inputting hand texture information according to an embodiment of the present invention
  • FIG. 2 is a schematic diagram of a user's hand image 101 collected and a plurality of image areas 111 obtained by dividing the user's hand image in the method 10 for inputting hand texture information in the embodiment shown in FIG. 1 of the present invention;
  • FIG. 3 is a flowchart of a method 20 for verifying hand texture information according to an embodiment of the present invention
  • FIG. 4 is a schematic diagram of a user hand image 201 collected and a plurality of image regions 211 obtained by dividing the user hand image in the method 20 for verifying hand texture information in the embodiment shown in FIG. 3 of the present invention
  • FIG. 5 is a structural block diagram of a device 30 for inputting hand texture information according to an embodiment of the present invention.
  • FIG. 6 is a structural block diagram of a verification device 40 for hand texture information according to an embodiment of the present invention.
  • FIG. 1 is a flowchart of a method 10 for inputting hand texture information according to an embodiment of the present invention.
  • the input method 10 may include: S11, collecting a user's hand image, the user's hand image including the user's finger texture information and palm texture information; S13, dividing the collected user's hand image into multiple Image regions, selecting a plurality of image regions satisfying preset entry conditions from the plurality of image regions, and extracting characteristic information of the plurality of image regions; and S15, storing the characteristic information of the plurality of image regions as a plurality of hands Part texture feature template.
  • collecting the user's hand image in S11 may include: when it is detected that the user touches or presses the hand texture information recognition module, controlling the hand texture information recognition module to collect the user's hand image.
  • the hand texture information recognition module may include a touch screen and an image acquisition module, and when it is detected that the user touches or presses the touch screen, the image acquisition module is controlled to collect an image of the user's hand.
  • collecting the user's hand image in S11 may further include: controlling the hand texture information recognition module to complete the matching process during the user's single touch or single pressing of the hand texture information recognition module.
  • the collection of an image of the user's hand Since the fingerprint data of a single finger contains limited feature information, the user often needs multiple touches or multiple presses to complete the entry of a complete fingerprint image data. However, the user’s hand is collected in the entry method 10 of the embodiment of the present invention.
  • the image includes both finger texture information and palm texture information. Therefore, a single touch or a single press of the user is sufficient to provide rich texture data of the user's hand without the need for multiple touches or multiple presses by the user. It greatly saves the user's time to participate in the input, and improves the input efficiency of the user's hand texture information.
  • the user may be prompted to touch or press again. Press the hand texture information recognition module again to re-acquire the user's hand image.
  • the input method 10 may further include: prompting the user with a preset mark to place at least part of the finger and at least part of the palm in the preset collection area. Specifically, the user can be prompted with a preset sign to place the entire hand in the preset collection area.
  • the preset sign may be the outline of a hand, for example, the outline of the hand may be displayed on the display screen of the terminal device that needs to be unlocked, so as to prompt the user to place the whole hand on the display screen to enter the identity information.
  • the collected user's hand image is divided into multiple image regions in S13. There may be multiple division methods here.
  • FIG. 2 shows one of the division methods.
  • the user's hand image 101 collected in S11 may be divided into a plurality of image regions 111 using a grid.
  • the multiple image areas 111 may be rectangular, and may have the same area.
  • the plurality of image areas 111 may also have other shapes, such as rhombus, triangle, hexagon, etc., which is not limited in the embodiment of the present invention.
  • dividing the collected user's hand image into multiple image areas 111 may include: dividing the collected user's hand according to a sample size required by a preset hand texture information verification algorithm.
  • the image is divided into a plurality of image regions 111, and the preset hand texture information verification algorithm is used to verify the hand texture information of the user to be verified according to the plurality of hand texture feature templates.
  • the size of each image area 111 may be equal to the sample size required by the preset hand texture information verification algorithm.
  • the number of the multiple image areas 111 depends on the size of the collected user's hand image. Image size and the sample size required by the preset hand texture information verification algorithm.
  • the input method is suitable for under-screen recognition of hand texture information, and the size of the collected user's hand image depends on the size of the screen touched by the user's hand.
  • the number of the plurality of image regions 111 obtained according to the dividing method shown in FIG. 2 may be 100 ⁇ 100, 128 ⁇ 128, or 148 ⁇ 148, but the embodiment of the present invention is not limited thereto.
  • selecting from the plurality of image regions in S13 several image regions that meet the preset input conditions may include: determining the image quality of each image region of the plurality of image regions And/or image area; selecting several image areas from the plurality of image areas whose image quality meets the preset image quality standard and/or the image area meets the preset image area standard.
  • determining the image quality of each image area in the plurality of image areas may include: using at least one image quality evaluation index to evaluate the image quality of each image area in the plurality of image areas , Get the quality evaluation value of each image area. Selecting several image areas whose image quality meets a preset image quality standard from the multiple image areas includes: selecting several image areas from the multiple image areas whose quality evaluation values are greater than a preset quality threshold.
  • the image quality evaluation index may include, but is not limited to: grayscale distribution, feature point distribution, image sharpness, image mean square error, entropy, edge retention, image signal-to-noise ratio, etc.
  • a larger number for example, 4 to 10
  • a smaller number for example, 1 to 3
  • image quality evaluation indicators may be used to evaluate the quality of the collected user's hand images.
  • the selected image quality evaluation indicators may be different.
  • appropriate algorithms can be used to calculate the image quality. For example, corresponding weights can be set for multiple image quality evaluation indicators, and the evaluation values corresponding to the multiple image quality evaluation indicators can be calculated first, and then the weighted average of the multiple image quality evaluation values can be obtained to obtain the final image quality evaluation value. .
  • the image quality evaluation value is the image The better the quality is, that is, selecting several image areas whose image quality meets the preset image quality standard from the multiple image areas may include: selecting several image areas whose quality evaluation values are less than the preset quality threshold from the multiple image areas
  • the image area is not limited in the embodiment of the present invention.
  • the image area may be the area of finger texture information or palm texture information contained in each image area, and several image areas whose image area meets a preset image area standard are selected from the plurality of image areas It may include: selecting several image areas with an image area greater than a preset area threshold from the multiple image areas. It is understandable that some image areas, such as the gap between adjacent fingers, contain less effective fingerprint data, so the collected data of this part of the image area can be selectively discarded.
  • the image area of each image area can be determined by using any appropriate area calculation algorithm, which is not limited in the embodiment of the present invention.
  • image areas with an image area ratio greater than a preset area ratio may also be selected from the plurality of image areas, and the image area ratio means that each image area contains finger texture information or palm texture information The area accounts for the percentage of the total area of the image area.
  • the preset area ratio may be 90%.
  • image quality and image area are used as a screening criterion for image regions that meet the preset input conditions.
  • it may not be limited to the above two screening criteria.
  • Those skilled in the art can also According to the actual situation, add other criteria for filtering the image area.
  • the area of the screen area covered by the user's hand determines the amount of data collected from the user's hand image, and then Affect the number of selected image areas that meet the preset input conditions.
  • the more image areas that meet the preset input conditions selected from the multiple image areas in S13 the more comprehensive the hand texture information entered, and the better the subsequent user identity verification effect will be .
  • extracting feature information of the plurality of image regions in S13 may include: extracting endpoints or bifurcation points of texture lines in the plurality of image regions, and any appropriate feature extraction algorithm may be used to extract the feature information
  • any appropriate feature extraction algorithm may be used to extract the feature information
  • the input method 10 may further include preprocessing the image data of the several image areas, such as noise reduction, normalization, and so on.
  • all the image data of the user's hand collected are divided into regions.
  • only the part of the image data containing texture information in the collected image data may be divided into regions to obtain multiple collections. sample.
  • the method for inputting hand texture information in the embodiment of the present invention can be applied to a variety of smart terminals, such as mobile phones and tablet computers.
  • the smart terminal includes multiple user identity entry and verification methods (for example, biotexture features, digital passwords, or graphic passwords, etc.)
  • the user can select the biotexture feature option to enter identity information. Since the entire hand has a relatively large contact area when entering, the method for entering hand texture information can be applied to a full-screen mobile terminal.
  • FIG. 3 is a flowchart of a method 20 for verifying hand texture information according to an embodiment of the present invention.
  • the verification method 20 may include: S21, collecting a user's hand image, the user's hand image including the user's finger texture information and palm texture information; S23, the collected user's hand image The hand image is divided into a plurality of image regions, and a plurality of image regions meeting preset verification conditions are selected from the plurality of image regions as a plurality of samples to be identified; S25, feature information of the plurality of samples to be identified is extracted, and all the samples are determined The degree of matching between the feature information of the plurality of samples to be identified and the plurality of pre-stored hand texture feature templates; and S27 according to the degree of matching between the feature information of the plurality of samples to be identified and the plurality of hand texture feature templates, A verification result of the user's hand texture information is generated.
  • collecting the user's hand image in S21 may include: when it is detected that the user touches or presses the hand texture information recognition module, controlling the hand texture information recognition module to collect the user's hand image.
  • the hand texture information recognition module may include a touch screen and an image acquisition module, and when it is detected that the user touches or presses the touch screen, the image acquisition module is controlled to collect an image of the user's hand.
  • collecting the user's hand image in S21 may further include: controlling the hand texture information recognition module to complete the matching process during the user's single touch or single pressing of the hand texture information recognition module.
  • the collection of an image of the user's hand may further include: controlling the hand texture information recognition module to complete the matching process during the user's single touch or single pressing of the hand texture information recognition module.
  • the collection of an image of the user's hand may further include: controlling the hand texture information recognition module to complete the matching process during the user's single touch or single pressing of the hand texture information recognition module. The collection of an image of the user's hand.
  • the contact area of the finger is limited.
  • the area pressed by the user's finger in the verification differs greatly from that in the input, it may cause the user's identity verification to fail. At this time, the user may need more Only one touch or pressing operation can be successfully verified, which brings inconvenience to the user experience.
  • the user can pass the entire Verification is performed in the way of hand contact, and the contact area of the whole hand is large, and the amount of data in the verification phase and the input phase overlaps with a large amount. Therefore, the probability of the user completing the verification through a single touch or a single press increases, which improves the verification efficiency , which improves the user experience.
  • the verification method 20 may further include: prompting the user with a preset mark to place the hand in the preset collection area.
  • the preset sign may be the outline of the hand, for example, the outline of the hand may be displayed on the display screen of the terminal device that needs to be unlocked to prompt the user to place the whole hand on the display screen for identification.
  • the preset collection area in the verification method 20 may be the same as the preset collection area in the hand texture information input method 10 of the foregoing embodiment.
  • the collected user's hand image is divided into multiple image regions in S23.
  • FIG. 4 shows one of the division methods.
  • the user's hand image 201 collected in S21 may be divided into a plurality of image regions 211 by using a grid.
  • the multiple image regions 211 may be rectangular, and may have the same area.
  • the multiple image areas 211 may also have other shapes, such as rhombus, triangle, hexagon, etc., which is not limited in the embodiment of the present invention.
  • dividing the collected user's hand image into multiple image areas 211 may include: dividing the collected user's hand according to a sample size required by a preset hand texture information verification algorithm.
  • the image is divided into a plurality of image areas 211.
  • the size of each image area 211 may be equal to the sample size required by the preset hand texture information verification algorithm.
  • the number of the multiple image areas 211 depends on the size of the collected user's hand image. Image size and the sample size required by the preset hand texture information verification algorithm.
  • the verification method is suitable for under-screen recognition of hand texture information, and the size of the collected user's hand image depends on the size of the screen touched by the user's hand.
  • the number of the plurality of image regions 211 obtained according to the dividing method shown in FIG. 4 may be 100 ⁇ 100, 128 ⁇ 128, or 148 ⁇ 148, but the embodiment of the present invention is not limited thereto.
  • selecting several image areas satisfying preset verification conditions from the multiple image areas as several samples to be identified in S23 may include: determining each of the multiple image areas Image quality and/or image area of the image area; selecting several image areas in the plurality of image areas whose image quality meets the preset image quality standard and/or the image area meets the preset image area standard as several samples to be identified .
  • determining the image quality of each image area in the plurality of image areas may include: using at least one image quality evaluation index to evaluate the image quality of each image area in the plurality of image areas , Obtain the quality evaluation value of each image area; selecting several image areas whose image quality meets the preset image quality standard in the multiple image areas as several samples to be identified includes: evaluating the quality of the multiple image areas Several image regions whose values are greater than a preset quality threshold are selected as a number of samples to be identified.
  • the image area is the area of finger texture information or palm texture information contained in each image area, and several image areas of the plurality of image areas whose image area meets a preset image area standard are selected as The plurality of samples to be identified includes: selecting a plurality of image regions with an image area greater than a preset area threshold in the plurality of image regions as the plurality of samples to be identified.
  • the image area ratio is that each image area contains a finger
  • the area of texture information or palm texture information accounts for the percentage of the total area of the image area.
  • the preset area ratio may be 70%.
  • the specific method for determining the image quality and/or image area of each image region in the multiple image regions can refer to the description of the corresponding part in the method for inputting hand texture information in the foregoing embodiment, here No longer.
  • extracting the feature information of the plurality of samples to be identified in S25 may include: extracting the endpoints or bifurcation points of the texture lines in the plurality of samples to be identified, and any appropriate feature extraction algorithm can be used to perform the feature information.
  • the embodiment of the present invention does not limit the extraction.
  • the verification method 20 may further include preprocessing the image data of the plurality of samples to be identified, such as noise reduction and normalization. Wait.
  • determining the degree of matching between the feature information of the plurality of samples to be identified and the plurality of pre-stored hand texture feature templates in S25 can be achieved by comparing the feature information of the plurality of samples to be identified with the pre-stored multiple hand texture feature information. This is achieved by comparing texture feature templates. For example, it can be determined one by one whether the feature information of each sample to be identified matches a certain feature template of the plurality of pre-stored hand texture feature templates.
  • any appropriate verification algorithm may be used to determine the degree of matching between the feature information of the plurality of samples to be identified and the plurality of pre-stored hand texture feature templates, which is not limited in the embodiment of the present invention.
  • the verification method 20 may further include: generating a plurality of pre-stored hand texture feature templates.
  • the multiple pre-stored hand texture feature templates may be generated using the hand texture information input method 10 of the embodiment shown in FIGS. 1 to 2.
  • the size of each image area obtained by dividing the collected user's hand image in the verification method 20 is the same as each image obtained by dividing the collected user's hand image in the input method 10
  • the size of the region is the same, which is equal to the sample size required by the preset hand texture information verification algorithm.
  • the number of multiple image areas obtained by dividing the collected user's hand image in the verification method 20 is the same as the multiple images obtained by dividing the collected user's hand image in the input method 10
  • the number of regions is the same.
  • the number of the plurality of pre-stored hand texture feature templates may be greater than or equal to the number of the plurality of samples to be identified.
  • generating the verification result of the hand texture information may include: If the feature information of the identification sample that has more than a predetermined number of samples to be identified matches the multiple pre-stored hand texture feature templates, it is determined that the hand texture information verification is passed, otherwise it is determined that the hand texture information verification fails .
  • the predetermined number can be set higher, and the user needs to put almost his entire hand in the collection area to generate a larger number of samples to be identified for matching.
  • the predetermined number can be set lower. At this time, the user only needs to place a part of the hand (for example, only the fingers or only the palm) in the collection area, and the verification can be completed .
  • all the image data of the user's hand collected are divided into regions.
  • only the part of the image data containing texture information in the collected image data may be divided into regions to obtain multiple collections. sample.
  • the area of the screen area covered by the user’s hand determines the length of the collected hand image data, which in turn affects the number of selected samples to be identified that meet the preset verification conditions. length.
  • the method for verifying hand texture information in the embodiment of the present invention can be applied to a variety of smart terminals, such as mobile phones and tablet computers.
  • the smart terminal includes multiple user identity entry and verification methods (for example, biotexture features, digital passwords, or graphic passwords, etc.)
  • the user can select the biotexture feature option to verify identity information. Since the entire hand has a relatively large contact area during verification, the verification method for hand texture information can be applied to a full-screen mobile terminal.
  • FIG. 5 is a structural block diagram of a hand texture information input device 30 according to an embodiment of the present invention.
  • the hand texture information input device 30 may include: an image acquisition module 31, configured to collect a user's hand image, the user's hand image may include the user's finger texture information and Palm texture information; processing module 32, used to divide the collected user's hand image into multiple image areas, select several image areas that meet preset input conditions from the multiple image areas, and extract the several images Region feature information; and a storage module 33, configured to store the feature information of the plurality of image regions as a plurality of hand texture feature templates.
  • the image acquisition module 31 may include: a screen (not shown) and a sensor (not shown).
  • the screen has a first surface suitable for contact with the user's hand, and A second surface opposite to a surface; the sensor is arranged on the second surface of the screen, and the sensor is adapted to collect the user's hand image in the entire screen range, that is, the sensor element of the sensor can be on the screen
  • One side covers the entire screen area to collect hand image signals from the full screen.
  • the starting coordinates of the sensor scan may be determined according to the touch area of the user's hand on the screen.
  • the screen may include a touch screen and an OLED display screen
  • the sensor may be a photoelectric sensor
  • the area of the photosensitive pixel array of the photoelectric sensor may be equal to or similar to the area of the screen.
  • the input device for hand texture information can be applied to a full-screen mobile terminal.
  • the respective functions and steps suitable for execution of the image acquisition module 31, the processing module 32 and the storage module 33 in the embodiment of the present invention may refer to the method for inputting hand texture information in the embodiment shown in FIG. 1 and FIG. 2
  • the description of related parts in 10 will not be repeated here.
  • FIG. 6 is a structural block diagram of an apparatus 40 for verifying hand texture information according to an embodiment of the present invention.
  • the hand texture information verification device 40 may include: an image acquisition module 41 for acquiring a user's hand image, the user's hand image including the user's finger texture information and palm Texture information; processing module 42, for dividing the collected user's hand image into multiple image regions, selecting from the multiple image regions a number of image regions meeting preset verification conditions as a number of samples to be identified, and extracting all The feature information of the plurality of samples to be identified, and confirm the degree of matching between the feature information of the plurality of samples to be identified and the plurality of pre-stored hand texture feature templates, and according to the feature information of the plurality of samples to be identified and the pre-stored
  • the matching degree of the multiple hand texture feature templates generates the verification result of the user's hand texture information
  • the storage module 43 is configured to store the multiple hand
  • the image acquisition module 41 may include: a screen (not shown) and a sensor (not shown).
  • the screen has a first surface suitable for contact with the user's hand, and A second surface opposite to a surface; the sensor is arranged on the second surface of the screen, and the sensor is adapted to collect the user's hand image in the entire screen range, that is, the sensor element of the sensor can be on the screen
  • One side covers the entire screen area to collect hand image signals from the full screen.
  • the starting coordinates of the sensor scan may be determined according to the touch area of the user's hand on the screen.
  • the screen may include a touch screen and an OLED display screen
  • the sensor may be a photoelectric sensor
  • the area of the photosensitive pixel array of the photoelectric sensor may be equal to or similar to the area of the screen.
  • the device for verifying hand texture information can be applied to a full-screen mobile terminal.
  • the texture information of the entire hand can be collected By dividing the collected user’s hand image into multiple image areas, it is convenient to process the image data by partition; selecting from the multiple image areas a number of image areas that meet the preset entry conditions, and extracting the number of image areas Feature information reduces the number of image areas where feature information needs to be extracted, thereby reducing the amount of calculation; storing the feature information of the several image areas as several hand texture feature templates to facilitate the subsequent verification of hand texture information.
  • the hand texture feature is divided into regions for comparison; since the multiple image regions are obtained by spatially dividing the user's hand image, some of the hand texture feature templates may only include fingers Texture information. Some feature templates may only include palm texture information, and some feature templates may include both finger texture information and palm texture information. Therefore, the user’s hand texture features obtained by the input method of hand texture information are more To enrich and lay a foundation for correspondingly improving the verification efficiency and verification security of hand texture information.
  • collecting the image of the user's hand further includes: controlling the hand texture information recognition module to complete the identification of the user's hand during the single touch or single pressing of the hand texture information recognition module by the user.
  • Image collection because the hand texture information input method can collect the user's full hand image, a single touch or a single press of the user is sufficient to provide rich user hand texture data, compared to the need for a single finger
  • the hand texture information entry method of the embodiment of the present invention greatly saves the user's time for participating in entry and improves the user's hand texture information The input efficiency.
  • the texture information of the entire hand can be collected By dividing the collected user’s hand image into multiple image areas, it is convenient for subsequent partition processing of image data and partition verification feature information; from the multiple image areas, a number of image areas meeting preset verification conditions are selected as a number of waiting Identifying the samples, extracting the feature information of the plurality of samples to be identified, reduces the number of image regions where feature information needs to be extracted, thereby reducing the amount of calculation.
  • the verification method of the embodiment of the present invention performs the verification of samples to be identified that contain a variety of different texture information. Authentication, the security of user identification is significantly improved.
  • collecting an image of the user’s hand may also include: controlling the hand texture information recognition module to complete the recognition of the user’s hand during a single touch or single pressing of the hand texture information recognition module by the user. Collection of internal images. Compared with the prior art when single-finger operation is used for verification, since the contact area of the finger is limited, the user may need to press multiple times to authenticate successfully.
  • the verification method of the embodiment of the present invention the user touches with the whole hand This method increases the probability that the user passes the verification with a single touch or a single press, that is, the verification efficiency is improved, and the user experience is improved.
  • generating a verification result of hand texture information according to the degree of matching between the feature information of the plurality of samples to be identified and the plurality of pre-stored hand texture feature templates may include: if the plurality of samples to be identified has more than If the feature information of the predetermined number of samples to be identified matches the multiple pre-stored hand texture feature templates, it is determined that the hand texture information verification has passed, otherwise it is determined that the hand texture information verification has failed, which is convenient for the user according to the actual situation.
  • the requirements of the security level in the application set the criteria for passing the verification. For example, if the security level for user verification is higher, the predetermined number can be set higher, otherwise, the predetermined number can be reduced.
  • the verification method in the embodiment of the present invention has high flexibility and is suitable for a variety of application scenarios.
  • the method for inputting and verifying hand texture information in the embodiment of the present invention can also solve the problem that users cannot perform fingerprint recognition due to the long-term wear of fingertip fingerprints, because the user can use texture information from other positions of the hand to complete the input and verification ,
  • the universality is enhanced.

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Abstract

一种手部纹理信息的录入方法和验证方法、录入装置和验证装置，所述录入方法包括：采集用户的手部图像，所述用户的手部图像包括所述用户的手指纹理信息和手掌纹理信息（S11）；将采集的用户的手部图像划分为多个图像区域，从所述多个图像区域中选取满足预设录入条件的若干图像区域，并提取所述若干图像区域的特征信息（S13）；以及将所述若干图像区域的特征信息存储为若干手部纹理特征模板（S15）。节省了用户进行录入和验证操作的时间，提高了用户录入和验证的效率；由于采集的用户的手部图像包括用户的手指纹理信息和手掌纹理信息，因此所述录入方法和验证方法、所述录入装置和验证装置的安全性显著提高。

Description

手部纹理信息的录入和验证方法、及录入和验证装置
本申请要求2019年5月29日提交中国专利局、申请号为201910460104.3、发明名称为“手部纹理信息的录入和验证方法、及录入和验证装置”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本发明涉及生物特征识别技术领域，尤其涉及一种手部纹理信息的录入方法和验证方法、录入装置和验证装置。
背景技术
随着智能终端技术的发展，出现了指纹录入和指纹识别的技术。指纹录入是预先采集用户的指纹并进行存储，当用户进行指纹识别时，将当前录入的指纹和预先存储的指纹进行比对，以验证用户身份。
然而，当前的指纹录入技术通常需要用户手指与录入界面的多次接触才能完成指纹数据的录入，指纹录入效率较低。此外，用户进行指纹认证时，单一的指纹数据包含的特征信息量有限，仍存在设备被误解锁的情况，用户的身份认证存在安全隐患。
因此，如何提高用户身份信息的录入效率、以及提高用户身份认证的安全性，是目前亟待解决的问题。
发明内容
本发明实施例提供一种手部纹理信息的录入方法，包括：采集用 户的手部图像，所述用户的手部图像包括所述用户的手指纹理信息和手掌纹理信息；将采集的用户的手部图像划分为多个图像区域，从所述多个图像区域中选取满足预设录入条件的若干图像区域，并提取所述若干图像区域的特征信息；以及将所述若干图像区域的特征信息存储为若干手部纹理特征模板。
可选地，从所述多个图像区域中选取满足预设录入条件的若干图像区域包括：确定所述多个图像区域中的每个图像区域的图像质量和/或图像面积；从所述多个图像区域中选取图像质量满足预设的图像质量标准和/或图像面积满足预设的图像面积标准的若干图像区域。
可选地，确定所述多个图像区域中的每个图像区域的图像质量包括：采用至少一种图像质量评价指标对所述多个图像区域中的每个图像区域进行图像质量评价，得到每个图像区域的质量评价值；从所述多个图像区域中选取图像质量满足预设的图像质量标准的若干图像区域包括：从所述多个图像区域中选取质量评价值大于预设质量阈值的若干图像区域。
可选地，所述图像面积为每个图像区域包含的手指纹理信息或手掌纹理信息的面积，从所述多个图像区域中选取图像面积满足预设的图像面积标准的若干图像区域包括：从所述多个图像区域中选取图像面积大于预设面积阈值、或图像面积比例大于预设面积比例阈值的若干图像区域。
可选地，采集用户的手部图像包括：当检测到用户触摸或按压手部纹理信息识别模块时，控制所述手部纹理信息识别模块采集所述用户的手部图像。
可选地，采集用户的手部图像还包括：在用户单次触摸或单次按压所述手部纹理信息识别模块的过程中，控制所述手部纹理信息识别模块完成对所述用户的手部图像的采集。
可选地，将采集的用户的手部图像划分为多个图像区域包括：根 据预设的手部纹理信息的验证算法要求的样本大小将采集的用户的手部图像划分为多个图像区域。
可选地，在采集用户的手部图像之前，所述录入方法还包括：以预设的标志提示用户将至少部分手指和至少部分手掌放在预设的采集区域内。
本发明实施例还提供一种手部纹理信息的验证方法，包括：采集用户的手部图像，所述用户的手部图像包括所述用户的手指纹理信息和手掌纹理信息；将采集的用户的手部图像划分为多个图像区域，从所述多个图像区域中选取满足预设验证条件的若干图像区域作为若干待识别样本；提取所述若干待识别样本的特征信息，并确定所述若干待识别样本的特征信息与预存的多个手部纹理特征模板的匹配程度；以及根据所述若干待识别样本的特征信息与所述预存的多个手部纹理特征模板的匹配程度，生成所述用户的手部纹理信息的验证结果。
可选地，从所述多个图像区域中选取若干图像区域作为若干待识别样本包括：确定所述多个图像区域中的每个图像区域的图像质量和/或图像面积；将所述多个图像区域中图像质量满足预设的图像质量标准和/或图像面积满足预设的图像面积标准的若干图像区域选取为若干待识别样本。
可选地，确定所述多个图像区域中的每个图像区域的图像质量包括：采用至少一种图像质量评价指标对所述多个图像区域中的每个图像区域进行图像质量评价，得到每个图像区域的质量评价值；将所述多个图像区域中图像质量满足预设的图像质量标准的若干图像区域选取为若干待识别样本包括：将所述多个图像区域中质量评价值大于预设质量阈值的若干图像区域选取为若干待识别样本。
可选地，所述图像面积为每个图像区域包含的手指纹理信息或手掌纹理信息的面积，将所述多个图像区域中图像面积满足预设的图像面积标准的若干图像区域选取为若干待识别样本包括：将所述多个图 像区域中图像面积大于预设面积阈值、或图像面积比例大于预设面积比例阈值的若干图像区域选取为若干待识别样本。
可选地，采集用户的手部图像包括：当检测到用户触摸或按压手部纹理信息识别模块时，控制所述手部纹理信息识别模块采集所述用户的手部图像。
可选地，采集用户的手部图像还包括：在用户单次触摸或单次按压所述手部纹理信息识别模块的过程中，控制所述手部纹理信息识别模块完成对所述用户的手部图像的采集。
可选地，在采集用户的手部图像之前，所述验证方法还包括：以预设的标志提示用户将手部放在预设的采集区域内。
可选地，将采集的用户的手部图像划分为多个图像区域包括：根据预设的手部纹理信息的验证算法要求的样本大小将采集的用户的手部图像划分为多个图像区域。
可选地，根据所述若干待识别样本的特征信息与所述预存的多个手部纹理特征模板的匹配程度，生成手部纹理信息的验证结果包括：若所述若干待识别样本中具有超过预定数目的待识别样本的特征信息与所述预存的多个手部纹理特征模板相匹配，则判定所述手部纹理信息验证通过，否则判定所述手部纹理信息验证失败。
可选地，所述验证方法还包括：采用本发明实施例的录入方法生成所述预存的多个手部纹理特征模板。
可选地，所述验证方法中的将采集的用户的手部图像划分得到的每个图像区域的尺寸与所述录入方法中将采集的用户的手部图像划分得到的每个图像区域的尺寸相同。
本发明实施例提供一种手部纹理信息的录入装置，包括：图像采集模块，用于采集用户的手部图像，所述用户的手部图像包括所述用户的手指纹理信息和手掌纹理信息；处理模块，用于将采集的用户的手部图像划分为多个图像区域，从所述多个图像区域中选取满足预设 录入条件的若干图像区域，并提取所述若干图像区域的特征信息；以及存储模块，用于将所述若干图像区域的特征信息存储为若干手部纹理特征模板。
可选地，所述图像采集模块包括：屏幕，所述屏幕具有适于用户的手部接触的第一表面、以及与所述第一表面相对的第二表面；以及传感器，设置于所述屏幕的第二表面，所述传感器适于在整个屏幕范围内采集用户的手部图像。
本发明实施例提供一种手部纹理信息的验证装置，包括：图像采集模块，用于采集用户的手部图像，所述用户的手部图像包括所述用户的手指纹理信息和手掌纹理信息；处理模块，用于将采集的用户的手部图像划分为多个图像区域，从所述多个图像区域中选取满足预设验证条件的若干图像区域作为若干待识别样本，提取所述若干待识别样本的特征信息，并确认所述若干待识别样本的特征信息与预存的多个手部纹理特征模板的匹配程度，以及根据所述若干待识别样本的特征信息与所述预存的多个手部纹理特征模板的匹配程度，生成所述用户的手部纹理信息的验证结果；以及存储模块，用于存储所述多个手部纹理特征模板。
可选地，所述图像采集模块包括：屏幕，所述屏幕具有适于用户的手部接触的第一表面、以及与所述第一表面相对的第二表面；以及传感器，设置于所述屏幕的第二表面，所述传感器适于在整个屏幕范围内采集用户的手部图像。
与现有技术相比，本发明实施例的技术方案具有以下有益效果：
在本发明实施例的手部纹理信息的录入方法和录入装置中，由于采集的用户的手部图像包括所述用户的手指纹理信息和手掌纹理信息，因而能够实现整只手的纹理信息的采集；通过将采集的用户的手部图像划分为多个图像区域，便于分区处理图像数据；从所述多个图像区域中选取满足预设录入条件的若干图像区域，并提取所述若干图像区域的特征信息，减少了需要提取特征信息的图像区域的数量，进 而降低运算量；将所述若干图像区域的特征信息存储为若干手部纹理特征模板，方便在后续手部纹理信息的验证过程中，将手部纹理特征分区域进行比对；由于所述多个图像区域是将用户的手部图像在空间上划分区域得到，因而所述若干手部纹理特征模板中有一部分特征模板可能仅包括手指纹理信息，有一部分特征模板可能仅包括手掌纹理信息，还有一部分特征模板可能同时包括手指纹理信息和手掌纹理信息，因而采用所述手部纹理信息的录入方法获取的用户的手部纹理特征更为丰富，为对应性地提高手部纹理信息的验证效率和验证安全性奠定了基础。
进一步地，采集用户的手部图像还包括：在用户单次触摸或单次按压所述手部纹理信息识别模块的过程中，控制所述手部纹理信息识别模块完成对所述用户的手部图像的采集，由于所述手部纹理信息的录入方法可以采集用户的全手图像，因此用户的单次触摸或单次按压，就足以提供丰富的用户手部纹理数据，相比于单手指需要多次触摸或多次按压才能完成一张完整的指纹图像数据的录入而言，本发明实施例的手部纹理信息的录入方法极大地节省了用户参与录入的时间，提高了用户手部纹理信息的录入效率。
在本发明实施例的手部纹理信息的验证方法和验证装置中，由于采集的用户的手部图像包括所述用户的手指纹理信息和手掌纹理信息，因而能够实现整只手的纹理信息的采集；通过将采集的用户的手部图像划分为多个图像区域，便于后续分区处理图像数据和分区验证特征信息；从所述多个图像区域中选取满足预设验证条件的若干图像区域作为若干待识别样本，提取所述若干待识别样本的特征信息，减少了需要提取特征信息的图像区域的数量，进而降低运算量。由于所述多个图像区域是将用户的手部图像在空间上划分区域得到，因而所述若干待识别样本中可能会有一部分待识别样本仅包括手指纹理信息，有一部分待识别样本仅包括手掌纹理信息，有一部分待识别样本同时包括手指纹理信息和手掌纹理信息，相比于单独的指纹或掌纹识别技术，本发明实施例的验证方法通过对包含多种不同纹理信息的待 识别样本的验证，用户身份识别的安全性显著提高。
进一步地，采集用户的手部图像还可以包括：在用户单次触摸或单次按压所述手部纹理信息识别模块的过程中，控制所述手部纹理信息识别模块完成对所述用户的手部图像的采集。相比于现有技术中采用单手指操作进行验证时，由于手指的接触面积有限，用户可能需要多次按压操作才能认证成功而言，本发明实施例的验证方法中用户通过整只手接触的方式进行验证，提高了用户单次触摸或单次按压通过验证的概率，即提高了验证效率，进而提升了用户体验。
进一步地，根据所述若干待识别样本的特征信息与所述预存的多个手部纹理特征模板的匹配程度，生成手部纹理信息的验证结果可以包括：若所述若干待识别样本中具有超过预定数目的待识别样本的特征信息与所述预存的多个手部纹理特征模板相匹配，则判定所述手部纹理信息验证通过，否则判定所述手部纹理信息验证失败，方便用户根据实际应用中安全级别的需求设定验证通过的标准，例如若对用户验证的安全级别要求较高，可以将所述预定数目设置得较高，反之则可以降低所述预定数目。本发明实施例的验证方法具有较高的灵活性，适用于多种应用场景。
本发明实施例的手部纹理信息的录入方法和验证方法，还可以解决用户因指尖指纹的长期磨损而无法进行指纹识别的问题，因为用户可以采用手部其它位置的纹理信息完成录入和验证，普适性增强。
附图说明
图1是本发明一个实施例的手部纹理信息的录入方法10的流程图；
图2是本发明图1所示实施例的手部纹理信息的录入方法10中，采集的用户手部图像101、以及将用户手部图像划分得到的多个图像区域111的示意图；
图3是本发明一个实施例的手部纹理信息的验证方法20的流程图；
图4是本发明图3所示实施例的手部纹理信息的验证方法20中，采集的用户手部图像201、以及将用户手部图像划分得到的多个图像区域211的示意图；
图5是本发明一个实施例的手部纹理信息的录入装置30的结构框图；以及
图6是本发明一个实施例的手部纹理信息的验证装置40的结构框图。
具体实施方式
为使本发明的上述目的、特征和有益效果能够更为明显易懂，下面结合附图对本发明的具体实施例做详细的说明。本发明由一些特定实施例来描述，然而本发明并非限定于此。任何本领域技术人员，在不脱离本发明的精神和范围内，均可作各种更动与修改。
本发明实施例提供一种手部纹理信息的录入方法。参考图1，图1是本发明一个实施例的手部纹理信息的录入方法10的流程图。所述录入方法10可以包括：S11，采集用户的手部图像，所述用户的手部图像包括所述用户的手指纹理信息和手掌纹理信息；S13，将采集的用户的手部图像划分为多个图像区域，从所述多个图像区域中选取满足预设录入条件的若干图像区域，并提取所述若干图像区域的特征信息；以及S15，将所述若干图像区域的特征信息存储为若干手部纹理特征模板。
在一些实施例中，S11中采集用户的手部图像可以包括：当检测到用户触摸或按压手部纹理信息识别模块时，控制所述手部纹理信息识别模块采集所述用户的手部图像。所述手部纹理信息识别模块可以包括触摸屏和图像采集模块，当检测到用户触摸或按压所述触摸屏 时，控制所述图像采集模块采集用户的手部图像。
在一些实施例中，S11中采集用户的手部图像还可以包括：在用户单次触摸或单次按压所述手部纹理信息识别模块的过程中，控制所述手部纹理信息识别模块完成对所述用户的手部图像的采集。由于单手指的指纹数据包含的特征信息有限，用户往往需要多次触摸或多次按压才能完成一张完整的指纹图像数据的录入，而本发明实施例的录入方法10中采集的用户的手部图像既包括手指纹理信息，又包括手掌纹理信息，因此用户的单次触摸或单次按压，就足以提供丰富的用户手部纹理数据，而无需用户的多次触摸或多次按压的操作，因而极大地节省了用户参与录入的时间，提高了用户手部纹理信息的录入效率。
在另一些实施例中，如果在用户单次触摸或单次按压过程中，所述手部纹理信息识别模块采集到的用户的手部图像达不到预设标准，那么可以提示用户再次触摸或再次按压所述手部纹理信息识别模块，以便重新采集用户的手部图像。其中用于衡量用户的手部图像是否达到预设标准的参数可以有多种，例如图像质量或图像面积。
在一些实施例中，在S11的采集用户的手部图像之前，所述录入方法10还可以包括：以预设的标志提示用户将至少部分手指和至少部分手掌放在预设的采集区域内。具体地，可以以预设的标志提示用户将整只手放在预设的采集区域内。所述预设的标志可以是手形的轮廓，例如可以在需要解锁的终端设备的显示屏上显示手形的轮廓，以提示用户将整只手放置于显示屏上进行身份信息的录入。
在一些实施例中，S13中将采集的用户的手部图像划分为多个图像区域，这里的划分方法可以有多种，图2示出了其中一种划分方法。结合参考图2，在一些实施例中，可以利用网格将S11中采集的用户的手部图像101划分为多个图像区域111。所述多个图像区域111可以为矩形，可以具有相同的面积。在其它实施例中，所述多个图像区域111也可以具有其它形状，例如菱形、三角形、六边形等，本发 明实施例对此不作限制。
在一些实施例中，将采集的用户的手部图像划分为多个图像区域111可以包括：根据预设的手部纹理信息的验证算法要求的样本大小(sample size)将采集的用户的手部图像划分为多个图像区域111，所述预设的手部纹理信息的验证算法用于根据所述若干手部纹理特征模板对待验证的用户的手部纹理信息进行验证。具体地，每个图像区域111的尺寸可以等于所述预设的手部纹理信息的验证算法要求的样本大小，此时所述多个图像区域111的数目取决于采集的用户的手部图像的尺寸(image size)和所述预设的手部纹理信息的验证算法要求的样本大小。
在一些实施例中，所述录入方法适用于手部纹理信息的屏下识别，则采集的用户的手部图像的大小取决于用户手部接触的屏幕的尺寸。
在一些实施例中，根据图2所示的划分方法得到的所述多个图像区域111的数目可以为100×100，128×128或148×148，然而本发明实施例不限于此。
继续参考图1，在一些实施例中，S13中从所述多个图像区域中选取满足预设录入条件的若干图像区域可以包括：确定所述多个图像区域中的每个图像区域的图像质量和/或图像面积；从所述多个图像区域中选取图像质量满足预设的图像质量标准和/或图像面积满足预设的图像面积标准的若干图像区域。
在一些实施例中，确定所述多个图像区域中的每个图像区域的图像质量可以包括：采用至少一种图像质量评价指标对所述多个图像区域中的每个图像区域进行图像质量评价，得到每个图像区域的质量评价值。从所述多个图像区域中选取图像质量满足预设的图像质量标准的若干图像区域包括：从所述多个图像区域中选取质量评价值大于预设质量阈值的若干图像区域。
在一些实施例中，所述图像质量评价指标可以包括但不限于：图像的灰度分布、特征点分布、图像清晰度、图像的均方差、熵、边缘保持度、图像信噪比等。在对图像质量评价要求较高的场合，可以采用较多数目(例如4至10个)的图像质量评价指标对采集的用户的手部图像的质量进行评价。而在对图像质量评价要求较低的场合，可以采用较少数目(例如1至3个)的图像质量评价指标对采集的用户的手部图像的质量进行评价。在不同的采集环境中，选取的图像质量评价指标可能不一样。对于选取的多种图像质量评价指标，可以采用适当的算法进行图像质量的计算。例如可以为多种图像质量评价指标分别设置相应的权重，先计算多种图像质量评价指标对应的评价值，再对所述多种图像质量评价值求加权平均，可以得到最终的图像质量评价值。
本实施例中定义得到的图像质量评价值越大，则图像质量越好，在其它实施例中，根据选取的图像质量评价指标的不同，也可以定义得到的图像质量评价值越小，则图像的质量越好，即从所述多个图像区域中选取图像质量满足预设的图像质量标准的若干图像区域可以包括：从所述多个图像区域中选取质量评价值小于预设质量阈值的若干图像区域，本发明实施例对此不作限制。
在一些实施例中，所述图像面积可以为每个图像区域包含的手指纹理信息或手掌纹理信息的面积，从所述多个图像区域中选取图像面积满足预设的图像面积标准的若干图像区域可以包括：从所述多个图像区域中选取图像面积大于预设面积阈值的若干图像区域。可以理解的是，某些图像区域例如相邻手指的间隙处，包含的有效指纹数据量较少，因而可以选择性地丢弃该部分图像区域的采集数据。每个图像区域的图像面积可以采用任意适当的面积计算算法确定，本发明实施例对此不作限制。
在其它实施例中，也可以从所述多个图像区域中选取图像面积比例大于预设面积比例的若干图像区域，所述图像面积比例即为每个图 像区域中包含手指纹理信息或手掌纹理信息的面积占所述图像区域的总面积的百分比。具体地，所述预设面积比例可以为90％。
需要说明的是，本实施例中以图像质量和图像面积作为满足预设录入条件的图像区域的一种筛选标准，在实际应用中，可以不限于上述两种筛选标准，本领域技术人员还可以根据实际情况增加其它用于筛选图像区域的标准。
在每个图像区域的尺寸固定的前提下，当用户通过触摸或按压屏幕进行手部纹理信息录入时，被用户手部覆盖的屏幕区域的面积决定了采集的用户手部图像的数据量，进而影响筛选出的满足预设录入条件的若干图像区域的数目。一般而言，S13中从所述多个图像区域中选取的满足预设录入条件的若干图像区域的数目越多，录入的手部纹理信息越全面，则后续用户进行身份验证的效果会更好。
在一些实施例中，S13中提取所述若干图像区域的特征信息可以包括：提取所述若干图像区域中的纹理线的端点或分叉点，可以采用任意适当的特征提取算法进行特征信息的提取，本发明实施例对此不作限制。
在一些实施例中，在提取所述若干图像区域的特征信息之前，所述录入方法10还可以包括对所述若干图像区域的图像数据进行预处理，例如降噪、归一化等。
上述实施例中是对采集的用户手部的所有图像数据进行区域划分，在其它实施例中，也可以仅对采集的图像数据中包含纹理信息的部分图像数据进行区域的划分，得到多个采集样本。
本发明实施例的手部纹理信息的录入方法可以应用于多种智能终端，例如手机、平板电脑等。当所述智能终端包括多种用户身份录入和验证方式(例如生物纹理特征、数字密码、或图形密码等)时，用户可以选择生物纹理特征选项进行身份信息的录入。由于整只手进行录入时的接触面积较大，所述手部纹理信息的录入方法可以应用于 全面屏移动终端。
本发明实施例还提供一种手部纹理信息的验证方法。参考图3，图3是本发明一个实施例的手部纹理信息的验证方法20的流程图。在一些实施例中，所述验证方法20可以包括：S21，采集用户的手部图像，所述用户的手部图像包括所述用户的手指纹理信息和手掌纹理信息；S23，将采集的用户的手部图像划分为多个图像区域，从所述多个图像区域中选取满足预设验证条件的若干图像区域作为若干待识别样本；S25，提取所述若干待识别样本的特征信息，并确定所述若干待识别样本的特征信息与预存的多个手部纹理特征模板的匹配程度；以及S27根据所述若干待识别样本的特征信息与所述预存的多个手部纹理特征模板的匹配程度，生成所述用户的手部纹理信息的验证结果。
在一些实施例中，S21中采集用户的手部图像可以包括：当检测到用户触摸或按压手部纹理信息识别模块时，控制所述手部纹理信息识别模块采集所述用户的手部图像。所述手部纹理信息识别模块可以包括触摸屏和图像采集模块，当检测到用户触摸或按压所述触摸屏时，控制所述图像采集模块采集用户的手部图像。
在一些实施例中，S21中采集用户的手部图像还可以包括：在用户单次触摸或单次按压所述手部纹理信息识别模块的过程中，控制所述手部纹理信息识别模块完成对所述用户的手部图像的采集。现有技术中采用单手指操作进行验证时，手指的接触面积有限，当用户在验证中手指按压的区域与录入中相差较大时，可能会造成用户身份验证的失败，此时用户可能需要多次触摸或按压操作才能验证成功，给用户体验带来不便，而本发明实施例的验证方法20中，由于采集的用户的手部图像包括手指纹理信息和手掌纹理信息，即用户可以通过整只手接触的方式进行验证，而整只手的接触面积较大，验证阶段和录入阶段重合的数据量较多，因而用户通过单次触摸或单次按压完成验证的概率增加，即提高了验证效率，进而提升了用户体验。
在一些实施例中，在S21的采集用户的手部图像之前，所述验证方法20还可以包括：以预设的标志提示用户将手部放在预设的采集区域内。所述预设的标志可以是手形的轮廓，例如可以在需要解锁的终端设备的显示屏上显示手形的轮廓，以提示用户将整只手放置于显示屏上进行身份识别。所述验证方法20中的预设采集区域可以与前述实施例的手部纹理信息的录入方法10中的预设的采集区域相同。
在一些实施例中，S23中将采集的用户的手部图像划分为多个图像区域，这里的划分方法可以有多种，图4示出了其中一种划分方法。结合参考图4，在一些实施例中，可以利用网格将S21中采集的用户的手部图像201划分为多个图像区域211。所述多个图像区域211可以为矩形，可以具有相同的面积。在其它实施例中，所述多个图像区域211也可以具有其它形状，例如菱形、三角形、六边形等，本发明实施例对此不作限制。
在一些实施例中，将采集的用户的手部图像划分为多个图像区域211可以包括：根据预设的手部纹理信息的验证算法要求的样本大小(sample size)将采集的用户的手部图像划分为多个图像区域211。具体地，每个图像区域211的尺寸可以等于所述预设的手部纹理信息的验证算法要求的样本大小，此时所述多个图像区域211的数目取决于采集的用户的手部图像的尺寸(image size)和所述预设的手部纹理信息的验证算法要求的样本大小。
在一些实施例中，所述验证方法适用于手部纹理信息的屏下识别，则采集的用户的手部图像的大小取决于用户手部接触的屏幕的尺寸。
在一些实施例中，根据图4所示的划分方法得到的所述多个图像区域211的数目可以为100×100，128×128或148×148，然而本发明实施例不限于此。
继续参考图3，在一些实施例中，S23中从所述多个图像区域中选取满足预设验证条件的若干图像区域作为若干待识别样本可以包 括：确定所述多个图像区域中的每个图像区域的图像质量和/或图像面积；将所述多个图像区域中图像质量满足预设的图像质量标准和/或图像面积满足预设的图像面积标准的若干图像区域选取为若干待识别样本。
在一些实施例中，确定所述多个图像区域中的每个图像区域的图像质量可以包括：采用至少一种图像质量评价指标对所述多个图像区域中的每个图像区域进行图像质量评价，得到每个图像区域的质量评价值；将所述多个图像区域中图像质量满足预设的图像质量标准的若干图像区域选取为若干待识别样本包括：将所述多个图像区域中质量评价值大于预设质量阈值的若干图像区域选取为若干待识别样本。
在一些实施例中，所述图像面积为每个图像区域包含的手指纹理信息或手掌纹理信息的面积，将所述多个图像区域中图像面积满足预设的图像面积标准的若干图像区域选取为若干待识别样本包括：将所述多个图像区域中图像面积大于预设面积阈值的若干图像区域选取为若干待识别样本。
在其它实施例中，也可以将所述多个图像区域中选取图像面积比例大于预设面积比例的若干图像区域选取为若干待识别样本，所述图像面积比例即为每个图像区域中包含手指纹理信息或手掌纹理信息的面积占所述图像区域的总面积的百分比。具体地，所述预设面积比例可以为70％。
本实施例中，确定所述多个图像区域中的每个图像区域的图像质量和/或图像面积的具体方法可以参照前述实施例的手部纹理信息的录入方法中对应部分的描述，此处不再赘述。
在一些实施例中，S25中提取所述若干待识别样本的特征信息可以包括：提取所述若干待识别样本中的纹理线的端点或分叉点，可以采用任意适当的特征提取算法进行特征信息的提取，本发明实施例对此不作限制。
在一些实施例中，在S25的提取所述若干待识别样本的特征信息之前，所述验证方法20还可以包括对所述若干待识别样本的图像数据进行预处理，例如降噪、归一化等。
在一些实施例中，S25中确定所述若干待识别样本的特征信息与预存的多个手部纹理特征模板的匹配程度可以通过将所述若干待识别样本的特征信息与预存的多个手部纹理特征模板进行比对来实现，例如可以逐一判断每个待识别样本的特征信息是否与所述预存的多个手部纹理特征模板中的某个特征模板相匹配。这里可以采用任意适当的验证算法进行所述若干待识别样本的特征信息与预存的多个手部纹理特征模板的匹配程度的判定，本发明实施例对此不作限制。
在一些实施例中，所述验证方法20还可以包括：生成预存的多个手部纹理特征模板。具体地，所述预存的多个手部纹理特征模板可以采用图1至图2所示实施例的手部纹理信息的录入方法10生成。
在一些实施例中，所述验证方法20中将采集的用户的手部图像划分得到的每个图像区域的尺寸与所述录入方法10中将采集的用户的手部图像划分得到的每个图像区域的尺寸相同，都等于预设的手部纹理信息的验证算法要求的样本大小。
在一些实施例中，所述验证方法20中将采集的用户的手部图像划分得到的多个图像区域的数目与所述录入方法10中将采集的用户的手部图像划分得到的多个图像区域的数目相同。
在一些实施例中，所述预存的多个手部纹理特征模板的数目可以大于或等于所述若干待识别样本的数目。
在一些实施例中，S27中根据所述若干待识别样本的特征信息与所述预存的多个手部纹理特征模板的匹配程度，生成手部纹理信息的验证结果可以包括：若所述若干待识别样本中具有超过预定数目的待识别样本的特征信息与所述预存的多个手部纹理特征模板相匹配，则判定所述手部纹理信息验证通过，否则判定所述手部纹理信息验证失 败。
对于一些安全认证级别较高的应用场合，可以将所述预定数目设置得较高，则用户需要将几乎整只手放在采集区域内，以产生较多数目的待识别样本进行匹配。而对于一些安全认证级别较低的应用场合，可以将所述预定数目设置得较低，此时用户仅需将手的一部分(例如仅手指或仅手掌)放置于采集区域内，也可以完成验证。
上述实施例中是对采集的用户手部的所有图像数据进行区域划分，在其它实施例中，也可以仅对采集的图像数据中包含纹理信息的部分图像数据进行区域的划分，得到多个采集样本。
当用户通过触摸或按压屏幕进行手部纹理信息验证时，用户手部覆盖的屏幕区域的面积决定了采集的手部图像数据长度，进而影响筛选出的满足预设验证条件的若干待识别样本的长度。
本发明实施例的手部纹理信息的验证方法可以应用于多种智能终端，例如手机、平板电脑等。当所述智能终端包括多种用户身份录入和验证方式(例如生物纹理特征、数字密码、或图形密码等)时，用户可以选择生物纹理特征选项进行身份信息的验证。由于整只手进行验证时的接触面积较大，所述手部纹理信息的验证方法可以应用于全面屏移动终端。
本发明实施例还提供一种手部纹理信息的录入装置。参考图5，图5是本发明一个实施例的手部纹理信息的录入装置30的结构框图。在一些实施例中，所述手部纹理信息的录入装置30可以包括：图像采集模块31，用于采集用户的手部图像，所述用户的手部图像可以包括所述用户的手指纹理信息和手掌纹理信息；处理模块32，用于将采集的用户的手部图像划分为多个图像区域，从所述多个图像区域中选取满足预设录入条件的若干图像区域，并提取所述若干图像区域的特征信息；以及存储模块33，用于将所述若干图像区域的特征信息存储为若干手部纹理特征模板。
在一些实施例中，所述图像采集模块31可以包括：屏幕(未示出)及传感器(未示出)，所述屏幕具有适于用户的手部接触的第一表面、以及与所述第一表面相对的第二表面；所述传感器设置于所述屏幕的第二表面，且所述传感器适于在整个屏幕范围内采集用户的手部图像，即所述传感器的传感元件可以在屏幕的一侧覆盖整个屏幕区域，以采集来自于全屏幕的手部图像信号。
在一些实施例中，所述传感器扫描的起始坐标可以根据用户手部在所述屏幕上的触摸区域确定。
在一些实施例中，所述屏幕可以包括触摸屏和OLED显示屏，所述传感器可以为光电传感器，所述光电传感器的感光像素阵列的面积可以和所述屏幕的面积相等或相近。所述手部纹理信息的录入装置可以应用于全面屏移动终端。
本发明实施例中的所述图像采集模块31、处理模块32和存储模块33各自的功能和适于执行的步骤可参照本发明图1和图2所示实施例的手部纹理信息的录入方法10中相关部分的描述，此处不再赘述。
本发明实施例还提供一种手部纹理信息的验证装置。参考图6，图6是本发明一个实施例的手部纹理信息的验证装置40的结构框图。在一些实施例中，所述手部纹理信息的验证装置40可以包括：图像采集模块41，用于采集用户的手部图像，所述用户的手部图像包括所述用户的手指纹理信息和手掌纹理信息；处理模块42，用于将采集的用户的手部图像划分为多个图像区域，从所述多个图像区域中选取满足预设验证条件的若干图像区域作为若干待识别样本，提取所述若干待识别样本的特征信息，并确认所述若干待识别样本的特征信息与预存的多个手部纹理特征模板的匹配程度，以及根据所述若干待识别样本的特征信息与所述预存的多个手部纹理特征模板的匹配程度，生成所述用户的手部纹理信息的验证结果；以及存储模块43，用于存储所述多个手部纹理特征模板。
在一些实施例中，所述图像采集模块41可以包括：屏幕(未示出)及传感器(未示出)，所述屏幕具有适于用户的手部接触的第一表面、以及与所述第一表面相对的第二表面；所述传感器设置于所述屏幕的第二表面，且所述传感器适于在整个屏幕范围内采集用户的手部图像，即所述传感器的传感元件可以在屏幕的一侧覆盖整个屏幕区域，以采集来自于全屏幕的手部图像信号。
在一些实施例中，所述传感器扫描的起始坐标可以根据用户手部在所述屏幕上的触摸区域确定。
在一些实施例中，所述屏幕可以包括触摸屏和OLED显示屏，所述传感器可以为光电传感器，所述光电传感器的感光像素阵列的面积可以和所述屏幕的面积相等或相近。所述手部纹理信息的验证装置可以应用于全面屏移动终端。
本发明实施例中的所述图像采集模块41、处理模块42和存储模块43各自的功能和适于执行的步骤可参照本发明图3和图4所示实施例的手部纹理信息的验证方法20中相关部分的描述，此处不再赘述。
在本发明实施例的手部纹理信息的录入方法和录入装置中，由于采集的用户的手部图像包括所述用户的手指纹理信息和手掌纹理信息，因而能够实现整只手的纹理信息的采集；通过将采集的用户的手部图像划分为多个图像区域，便于分区处理图像数据；从所述多个图像区域中选取满足预设录入条件的若干图像区域，并提取所述若干图像区域的特征信息，减少了需要提取特征信息的图像区域的数量，进而降低运算量；将所述若干图像区域的特征信息存储为若干手部纹理特征模板，方便在后续手部纹理信息的验证过程中，将手部纹理特征分区域进行比对；由于所述多个图像区域是将用户的手部图像在空间上划分区域得到，因而所述若干手部纹理特征模板中有一部分特征模板可能仅包括手指纹理信息，有一部分特征模板可能仅包括手掌纹理信息，还有一部分特征模板可能同时包括手指纹理信息和手掌纹理信 息，因而采用所述手部纹理信息的录入方法获取的用户的手部纹理特征更为丰富，为对应性地提高手部纹理信息的验证效率和验证安全性奠定了基础。
进一步地，采集用户的手部图像还包括：在用户单次触摸或单次按压所述手部纹理信息识别模块的过程中，控制所述手部纹理信息识别模块完成对所述用户的手部图像的采集，由于所述手部纹理信息的录入方法可以采集用户的全手图像，因此用户的单次触摸或单次按压，就足以提供丰富的用户手部纹理数据，相比于单手指需要多次触摸或多次按压才能完成一张完整的指纹图像数据的录入而言，本发明实施例的手部纹理信息的录入方法极大地节省了用户参与录入的时间，提高了用户手部纹理信息的录入效率。
在本发明实施例的手部纹理信息的验证方法和验证装置中，由于采集的用户的手部图像包括所述用户的手指纹理信息和手掌纹理信息，因而能够实现整只手的纹理信息的采集；通过将采集的用户的手部图像划分为多个图像区域，便于后续分区处理图像数据和分区验证特征信息；从所述多个图像区域中选取满足预设验证条件的若干图像区域作为若干待识别样本，提取所述若干待识别样本的特征信息，减少了需要提取特征信息的图像区域的数量，进而降低运算量。由于所述多个图像区域是将用户的手部图像在空间上划分区域得到，因而所述若干待识别样本中可能会有一部分待识别样本仅包括手指纹理信息，有一部分待识别样本仅包括手掌纹理信息，有一部分待识别样本同时包括手指纹理信息和手掌纹理信息，相比于单独的指纹或掌纹识别技术，本发明实施例的验证方法通过对包含多种不同纹理信息的待识别样本的验证，用户身份识别的安全性显著提高。
进一步地，采集用户的手部图像还可以包括：在用户单次触摸或单次按压所述手部纹理信息识别模块的过程中，控制所述手部纹理信息识别模块完成对所述用户的手部图像的采集。相比于现有技术中采用单手指操作进行验证时，由于手指的接触面积有限，用户可能需要 多次按压操作才能认证成功而言，本发明实施例的验证方法中用户通过整只手接触的方式进行验证，提高了用户单次触摸或单次按压通过验证的概率，即提高了验证效率，进而提升了用户体验。
进一步地，根据所述若干待识别样本的特征信息与所述预存的多个手部纹理特征模板的匹配程度，生成手部纹理信息的验证结果可以包括：若所述若干待识别样本中具有超过预定数目的待识别样本的特征信息与所述预存的多个手部纹理特征模板相匹配，则判定所述手部纹理信息验证通过，否则判定所述手部纹理信息验证失败，方便用户根据实际应用中安全级别的需求设定验证通过的标准，例如若对用户验证的安全级别要求较高，可以将所述预定数目设置得较高，反之则可以降低所述预定数目。本发明实施例的验证方法具有较高的灵活性，适用于多种应用场景。
本发明实施例的手部纹理信息的录入方法和验证方法，还可以解决用户因指尖指纹的长期磨损而无法进行指纹识别的问题，因为用户可以采用手部其它位置的纹理信息完成录入和验证，普适性增强。
虽然本发明披露如上，但本发明并非限定于此。任何本领域技术人员，在不脱离本发明的精神和范围内，均可作各种更动与修改，因此本发明的保护范围应当以权利要求所限定的范围为准。

Claims (23)

  1. 一种手部纹理信息的录入方法，其特征在于，包括：
    采集用户的手部图像，所述用户的手部图像包括所述用户的手指纹理信息和手掌纹理信息；
    将采集的用户的手部图像划分为多个图像区域，从所述多个图像区域中选取满足预设录入条件的若干图像区域，并提取所述若干图像区域的特征信息；以及
    将所述若干图像区域的特征信息存储为若干手部纹理特征模板。
  2. 如权利要求1所述的录入方法，其特征在于，从所述多个图像区域中选取满足预设录入条件的若干图像区域包括：
    确定所述多个图像区域中的每个图像区域的图像质量和/或图像面积；
    从所述多个图像区域中选取图像质量满足预设的图像质量标准和/或图像面积满足预设的图像面积标准的若干图像区域。
  3. 如权利要求2所述的录入方法，其特征在于，确定所述多个图像区域中的每个图像区域的图像质量包括：采用至少一种图像质量评价指标对所述多个图像区域中的每个图像区域进行图像质量评价，得到每个图像区域的质量评价值；
    从所述多个图像区域中选取图像质量满足预设的图像质量标准的若干图像区域包括：从所述多个图像区域中选取质量评价值大于预设质量阈值的若干图像区域。
  4. 如权利要求2所述的录入方法，其特征在于，所述图像面积为每个图像区域包含的手指纹理信息或手掌纹理信息的面积，从所述多个图像区域中选取图像面积满足预设的图像面积标准的若干图像区域包括：从所述多个图像区域中选取图像面积大于预设面积阈值、或图像面积比例大于预设面积比例阈值的若干图像区域。
  5. 如权利要求1所述的录入方法，其特征在于，采集用户的手部图像包括：当检测到用户触摸或按压手部纹理信息识别模块时，控制所述手部纹理信息识别模块采集所述用户的手部图像。
  6. 如权利要求5所述的录入方法，其特征在于，采集用户的手部图像还包括：在用户单次触摸或单次按压所述手部纹理信息识别模块的过程中，控制所述手部纹理信息识别模块完成对所述用户的手部图像的采集。
  7. 如权利要求1所述的录入方法，其特征在于，将采集的用户的手部图像划分为多个图像区域包括：根据预设的手部纹理信息的验证算法要求的样本大小将采集的用户的手部图像划分为多个图像区域。
  8. 如权利要求1所述的录入方法，其特征在于，在采集用户的手部图像之前，所述录入方法还包括：以预设的标志提示用户将至少部分手指和至少部分手掌放在预设的采集区域内。
  9. 一种手部纹理信息的验证方法，其特征在于，包括：
    采集用户的手部图像，所述用户的手部图像包括所述用户的手指纹理信息和手掌纹理信息；
    将采集的用户的手部图像划分为多个图像区域，从所述多个图像区域中选取满足预设验证条件的若干图像区域作为若干待识别样本；
    提取所述若干待识别样本的特征信息，并确定所述若干待识别样本的特征信息与预存的多个手部纹理特征模板的匹配程度；以及
    根据所述若干待识别样本的特征信息与所述预存的多个手部纹理特征模板的匹配程度，生成所述用户的手部纹理信息的验证结果。
  10. 根据权利要求9所述的验证方法，其特征在于，从所述多个图像区域中选取若干图像区域作为若干待识别样本包括：
    确定所述多个图像区域中的每个图像区域的图像质量和/或图像面积；
    将所述多个图像区域中图像质量满足预设的图像质量标准和/或图像面积满足预设的图像面积标准的若干图像区域选取为若干待识别样本。
  11. 根据权利要求10所述的验证方法，其特征在于，确定所述多个图像区域中的每个图像区域的图像质量包括：采用至少一种图像质量评价指标对所述多个图像区域中的每个图像区域进行图像质量评价，得到每个图像区域的质量评价值；
    将所述多个图像区域中图像质量满足预设的图像质量标准的若干图像区域选取为若干待识别样本包括：将所述多个图像区域中质量评价值大于预设质量阈值的若干图像区域选取为若干待识别样本。
  12. 根据权利要求10所述的验证方法，其特征在于，所述图像面积为每个图像区域包含的手指纹理信息或手掌纹理信息的面积，将所述多个图像区域中图像面积满足预设的图像面积标准的若干图像区域选取为若干待识别样本包括：将所述多个图像区域中图像面积大于预设面积阈值、或图像面积比例大于预设面积比例阈值的若干图像区域选取为若干待识别样本。
  13. 根据权利要求9所述的验证方法，其特征在于，采集用户的手部图像包括：当检测到用户触摸或按压手部纹理信息识别模块时，控制所述手部纹理信息识别模块采集所述用户的手部图像。
  14. 根据权利要求13所述的验证方法，其特征在于，采集用户的手部图像还包括：在用户单次触摸或单次按压所述手部纹理信息识别模块的过程中，控制所述手部纹理信息识别模块完成对所述用户的手部图像的采集。
  15. 根据权利要求9所述的验证方法，其特征在于，在采集用户的手部图像之前，所述验证方法还包括：以预设的标志提示用户将手部放在预设的采集区域内。
  16. 根据权利要求9所述的验证方法，其特征在于，将采集的用户的 手部图像划分为多个图像区域包括：根据预设的手部纹理信息的验证算法要求的样本大小将采集的用户的手部图像划分为多个图像区域。
  17. 根据权利要求9所述的验证方法，其特征在于，根据所述若干待识别样本的特征信息与所述预存的多个手部纹理特征模板的匹配程度，生成手部纹理信息的验证结果包括：
    若所述若干待识别样本中具有超过预定数目的待识别样本的特征信息与所述预存的多个手部纹理特征模板相匹配，则判定所述手部纹理信息验证通过，否则判定所述手部纹理信息验证失败。
  18. 根据权利要求9所述的验证方法，其特征在于，还包括：采用如权利要求1至8任一项所述的录入方法生成所述预存的多个手部纹理特征模板。
  19. 根据权利要求18所述的验证方法，其特征在于，所述验证方法中的将采集的用户的手部图像划分得到的每个图像区域的尺寸与所述录入方法中将采集的用户的手部图像划分得到的每个图像区域的尺寸相同。
  20. 一种手部纹理信息的录入装置，其特征在于，包括：
    图像采集模块，用于采集用户的手部图像，所述用户的手部图像包括所述用户的手指纹理信息和手掌纹理信息；
    处理模块，用于将采集的用户的手部图像划分为多个图像区域，从所述多个图像区域中选取满足预设录入条件的若干图像区域，并提取所述若干图像区域的特征信息；以及
    存储模块，用于将所述若干图像区域的特征信息存储为若干手部纹理特征模板。
  21. 根据权利要求20所述的录入装置，其特征在于，所述图像采集模块包括：
    屏幕，所述屏幕具有适于用户的手部接触的第一表面、以及与所 述第一表面相对的第二表面；以及
    传感器，设置于所述屏幕的第二表面，所述传感器适于在整个屏幕范围内采集用户的手部图像。
  22. 一种手部纹理信息的验证装置，其特征在于，包括：
    图像采集模块，用于采集用户的手部图像，所述用户的手部图像包括所述用户的手指纹理信息和手掌纹理信息；
    处理模块，用于将采集的用户的手部图像划分为多个图像区域，从所述多个图像区域中选取满足预设验证条件的若干图像区域作为若干待识别样本，提取所述若干待识别样本的特征信息，并确认所述若干待识别样本的特征信息与预存的多个手部纹理特征模板的匹配程度，以及根据所述若干待识别样本的特征信息与所述预存的多个手部纹理特征模板的匹配程度，生成所述用户的手部纹理信息的验证结果；以及
    存储模块，用于存储所述多个手部纹理特征模板。
  23. 根据权利要求22所述的验证装置，其特征在于，所述图像采集模块包括：
    屏幕，所述屏幕具有适于用户的手部接触的第一表面、以及与所述第一表面相对的第二表面；以及
    传感器，设置于所述屏幕的第二表面，所述传感器适于在整个屏幕范围内采集用户的手部图像。
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