CN104899582A - Fingerprint identification software and fingerprint identification method therefor - Google Patents
Fingerprint identification software and fingerprint identification method therefor Download PDFInfo
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- CN104899582A CN104899582A CN201510376332.4A CN201510376332A CN104899582A CN 104899582 A CN104899582 A CN 104899582A CN 201510376332 A CN201510376332 A CN 201510376332A CN 104899582 A CN104899582 A CN 104899582A
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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
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Abstract
The invention discloses fingerprint identification software and a fingerprint identification method therefor. The fingerprint identification software is installed in a mobile telephone and comprises a setting module, a fingerprint entering module, a storage module and a fingerprint matching module, wherein the fingerprint entering module is used for entering a verification fingerprint; both the setting module and the fingerprint matching module are in communication connection with the storage module, the fingerprint entering module is in communication connection with the fingerprint matching module, and the fingerprint matching module is also in communication connection with a control module of the mobile telephone. According to the fingerprint identification software and the fingerprint identification method therefor, different similarities can be set for applications with different security level requirements; by setting relatively low similarity for the applications with relatively low security level requirements, the success rate of fingerprint identification can be increased; by setting relatively high similarity for the applications with relatively high security level requirements, the accuracy of fingerprint identification can be enhanced; and thus different requirements of different applications on security level are met.
Description
Technical field
The present invention relates to field of information security technology, particularly relate to a kind of fingerprint identification software and fingerprint identification method thereof.
Background technology
Current, the mobile phone that people use usually all does not have cell-phone lock or with the cell-phone lock arranging password, for the former mobile phone, quite low to the personal secrets protection of user, once lose, the privacy of user is very easily known by people; For the latter, open mobile phone all needs to input password at every turn, and input by mistake and also need to re-enter, even repeatedly input can cause mobile phone lock, does not access to your password for a long time what is more the situation such as to forget and also happen occasionally, quite inconvenient.
Summary of the invention
The object of the invention is to overcome the deficiencies in the prior art, a kind of fingerprint identification software and fingerprint identification method thereof are provided, the different requirements of different application to safe class can be met.
The object of the invention is to be achieved through the following technical solutions: a kind of fingerprint identification software, be installed on mobile phone, comprise and module, the fingerprint typing module verifying fingerprint for typing, memory module and fingerprint matching module are set, arrange module to be all connected with memory module communication with fingerprint matching module, fingerprint typing module is connected with fingerprint matching module communication, and fingerprint matching module is also connected with the control module communication of mobile phone.
The described module that arranges comprises and unlocks fingerprint and arrange submodule and program safety grade arranges submodule, unlock fingerprint and arrange submodule for arranging the unblock fingerprint of each application program on mobile phone, program safety grade arranges submodule for arranging the safe class of each application program on mobile phone.
Described fingerprint matching module comprises image procossing submodule, comparer module and information and sends submodule.
The unblock fingerprint image that described image procossing submodule reception memory module sends over and the checking fingerprint image that fingerprint typing module sends over, and the first fingerprint feature point is extracted from unblock fingerprint image, extract the second fingerprint feature point from checking fingerprint image.
Comparer module obtains the first fingerprint feature point and the second fingerprint feature point from image procossing submodule, and need fingerprint recognition to carry out the safe class of the application program of certification from memory module acquisition, and the first similarity reached needed for the success of safe class determination fingerprint recognition, and the first fingerprint feature point and the second fingerprint feature point are contrasted, calculate the second similarity of the first fingerprint feature point and the second fingerprint feature point, if the second similarity is not less than the first similarity, then fingerprint recognition success.
Information sends the control module that successful for fingerprint recognition information is sent to mobile phone by submodule.
A kind of fingerprint identification method, comprises the following steps:
S1., the safe class unlocking fingerprint and application program is set;
S2. gather checking fingerprint, contrast unlocks fingerprint and checking fingerprint, obtains the second similarity;
S3. the first similarity that the safe class of application program is corresponding is obtained, if the second similarity is not less than the first similarity, then fingerprint recognition success.
Safe class described in step S1 comprises ordinary grade, important level and confidential, and the first similarity corresponding to ordinary grade is 80%, and the second similarity corresponding to important level is 90%, and the first similarity corresponding to confidential is 95%.
Step S2 comprises following sub-step:
S21. fingerprint typing module acquires checking fingerprint image, and this checking fingerprint image is sent to image procossing submodule;
S22. image procossing submodule obtains from memory module and unlocks fingerprint image, and carries out Image semantic classification to unblock fingerprint image and checking fingerprint image;
S23. image procossing submodule extracts the first fingerprint feature point from unblock fingerprint image, extracts the second fingerprint feature point from checking fingerprint image;
S24. the first fingerprint feature point and the second fingerprint feature point contrast by comparer module, calculate the second similarity of the first fingerprint feature point and the second fingerprint feature point.
Step S3 comprises following sub-step:
S31. comparer module obtains from memory module needs fingerprint recognition to carry out the safe class of the application program of certification, and the first similarity reached needed for the success of safe class determination fingerprint recognition;
S32. the first similarity and the second similarity is compared, if the second similarity is not less than the first similarity, then fingerprint recognition success.
In step S22, Image semantic classification comprises following sub-step:
S221. gray processing process is carried out to unblock fingerprint image and checking fingerprint image;
S222. threshold segmentation process is carried out to unblock fingerprint image and checking fingerprint image;
S223. gray balance process is carried out to unblock fingerprint image and checking fingerprint image;
S224. to unblock fingerprint image and the smoothing filtering process of checking fingerprint image;
S225. binary conversion treatment is carried out to unblock fingerprint image and checking fingerprint image;
S226. thinning processing is carried out to unblock fingerprint image and checking fingerprint image.
The invention has the beneficial effects as follows: for safe class, the present invention can require that different application programs arranges different similarities, lower application program is required for safe class, lower similarity is set, the success ratio of fingerprint recognition can be improved, for the application program that safe class is higher, higher similarity is set, the accuracy rate of fingerprint recognition can be strengthened, thus meet the different requirements of different application to safe class.
Accompanying drawing explanation
Fig. 1 is the structured flowchart of a kind of fingerprint identification software of the present invention;
Fig. 2 is the process flow diagram of a kind of fingerprint identification method of the present invention.
Embodiment
Below in conjunction with accompanying drawing, technical scheme of the present invention is described in further detail, but protection scope of the present invention is not limited to the following stated.
As shown in Figure 1, a kind of fingerprint identification software, be installed on mobile phone, comprise and module, the fingerprint typing module verifying fingerprint for typing, memory module and fingerprint matching module are set, arrange module to be all connected with memory module communication with fingerprint matching module, fingerprint typing module is connected with fingerprint matching module communication, and fingerprint matching module is also connected with the control module communication of mobile phone.
The described module that arranges comprises and unlocks fingerprint and arrange submodule and program safety grade arranges submodule, unlock fingerprint and arrange submodule for arranging the unblock fingerprint of each application program on mobile phone, program safety grade arranges submodule for arranging the safe class of each application program on mobile phone.
Described fingerprint typing module is used for typing checking fingerprint, and checking fingerprint image is sent to fingerprint matching module.
Described memory module unlocks the safety level information of fingerprint image and each application program for storing.
Described fingerprint matching module comprises image procossing submodule, comparer module and information and sends submodule.
The unblock fingerprint image that described image procossing submodule reception memory module sends over and the checking fingerprint image that fingerprint typing module sends over, and the first fingerprint feature point is extracted from unblock fingerprint image, extract the second fingerprint feature point from checking fingerprint image.
Described comparer module obtains the first fingerprint feature point and the second fingerprint feature point from image procossing submodule, and need fingerprint recognition to carry out the safe class of the application program of certification from memory module acquisition, and the first similarity reached needed for the success of safe class determination fingerprint recognition, and the first fingerprint feature point and the second fingerprint feature point are contrasted, calculate the second similarity of the first fingerprint feature point and the second fingerprint feature point, if the second similarity is not less than the first similarity, then fingerprint recognition success.
Described information sends the control module that successful for fingerprint recognition information is sent to mobile phone by submodule.
As shown in Figure 2, a kind of fingerprint identification method, comprises the following steps:
S1., the safe class unlocking fingerprint and application program is set.Arranging when unlocking fingerprint needs multi collect to unlock fingerprint image, therefrom chooses the unblock fingerprint image that image the most clearly uses as subsequent step, to improve the accuracy of fingerprint recognition.
Described safe class comprises ordinary grade, important level and confidential, and the first similarity corresponding to ordinary grade is 80%, and the second similarity corresponding to important level is 90%, and the first similarity corresponding to confidential is 95%.
S2. gather checking fingerprint, contrast unlocks fingerprint and checking fingerprint, obtains the second similarity.
Step S2 comprises following sub-step:
S21. fingerprint typing module acquires checking fingerprint image, and this checking fingerprint image is sent to image procossing submodule.
S22. image procossing submodule obtains from memory module and unlocks fingerprint image, and carries out Image semantic classification to unblock fingerprint image and checking fingerprint image.
In step S22, Image semantic classification comprises following sub-step:
S221. gray processing process is carried out to unblock fingerprint image and checking fingerprint image.
S222. threshold segmentation process is carried out to unblock fingerprint image and checking fingerprint image.
S223. gray balance process is carried out to unblock fingerprint image and checking fingerprint image.
S224. to unblock fingerprint image and the smoothing filtering process of checking fingerprint image.
S225. binary conversion treatment is carried out to unblock fingerprint image and checking fingerprint image.
S226. thinning processing is carried out to unblock fingerprint image and checking fingerprint image.
S23. image procossing submodule extracts the first fingerprint feature point from unblock fingerprint image, extracts the second fingerprint feature point from checking fingerprint image.
S24. the first fingerprint feature point and the second fingerprint feature point contrast by comparer module, calculate the second similarity of the first fingerprint feature point and the second fingerprint feature point.
S3. the first similarity that the safe class of application program is corresponding is obtained, if the second similarity is not less than the first similarity, then fingerprint recognition success.
Step S3 comprises following sub-step:
S31. comparer module obtains from memory module needs fingerprint recognition to carry out the safe class of the application program of certification, and the first similarity reached needed for the success of safe class determination fingerprint recognition.
S32. the first similarity and the second similarity is compared, if the second similarity is not less than the first similarity, then fingerprint recognition success.
Claims (8)
1. a fingerprint identification software, be installed on mobile phone, it is characterized in that: comprise and module, the fingerprint typing module verifying fingerprint for typing, memory module and fingerprint matching module are set, arrange module to be all connected with memory module communication with fingerprint matching module, fingerprint typing module is connected with fingerprint matching module communication, and fingerprint matching module is also connected with the control module communication of mobile phone.
2. a kind of fingerprint identification software according to claim 1, it is characterized in that: the described module that arranges comprises and unlocks fingerprint and arrange submodule and program safety grade arranges submodule, unlock fingerprint and arrange submodule for arranging the unblock fingerprint of each application program on mobile phone, program safety grade arranges submodule for arranging the safe class of each application program on mobile phone.
3. a kind of fingerprint identification software according to claim 1, is characterized in that: described fingerprint matching module comprises image procossing submodule, comparer module and information and sends submodule;
The unblock fingerprint image that described image procossing submodule reception memory module sends over and the checking fingerprint image that fingerprint typing module sends over, and the first fingerprint feature point is extracted from unblock fingerprint image, extract the second fingerprint feature point from checking fingerprint image;
Comparer module obtains the first fingerprint feature point and the second fingerprint feature point from image procossing submodule, and need fingerprint recognition to carry out the safe class of the application program of certification from memory module acquisition, and the first similarity reached needed for the success of safe class determination fingerprint recognition, and the first fingerprint feature point and the second fingerprint feature point are contrasted, calculate the second similarity of the first fingerprint feature point and the second fingerprint feature point, if the second similarity is not less than the first similarity, then fingerprint recognition success;
Information sends the control module that successful for fingerprint recognition information is sent to mobile phone by submodule.
4. a fingerprint identification method, is characterized in that: comprise the following steps:
S1., the safe class unlocking fingerprint and application program is set;
S2. gather checking fingerprint, contrast unlocks fingerprint and checking fingerprint, obtains the second similarity;
S3. the first similarity that the safe class of application program is corresponding is obtained, if the second similarity is not less than the first similarity, then fingerprint recognition success.
5. a kind of fingerprint identification method according to claim 4, it is characterized in that: safe class described in step S1 comprises ordinary grade, important level and confidential, first similarity corresponding to ordinary grade is 80%, second similarity corresponding to important level is 90%, and the first similarity corresponding to confidential is 95%.
6. a kind of fingerprint identification method according to claim 4, is characterized in that: step S2 comprises following sub-step:
S21. fingerprint typing module acquires checking fingerprint image, and this checking fingerprint image is sent to image procossing submodule;
S22. image procossing submodule obtains from memory module and unlocks fingerprint image, and carries out Image semantic classification to unblock fingerprint image and checking fingerprint image;
S23. image procossing submodule extracts the first fingerprint feature point from unblock fingerprint image, extracts the second fingerprint feature point from checking fingerprint image;
S24. the first fingerprint feature point and the second fingerprint feature point contrast by comparer module, calculate the second similarity of the first fingerprint feature point and the second fingerprint feature point.
7. a kind of fingerprint identification method according to claim 4, is characterized in that: step S3 comprises following sub-step:
S31. comparer module obtains from memory module needs fingerprint recognition to carry out the safe class of the application program of certification, and the first similarity reached needed for the success of safe class determination fingerprint recognition;
S32. the first similarity and the second similarity is compared, if the second similarity is not less than the first similarity, then fingerprint recognition success.
8. a kind of fingerprint identification method according to claim 6, is characterized in that: in step S22, Image semantic classification comprises following sub-step:
S221. gray processing process is carried out to unblock fingerprint image and checking fingerprint image;
S222. threshold segmentation process is carried out to unblock fingerprint image and checking fingerprint image;
S223. gray balance process is carried out to unblock fingerprint image and checking fingerprint image;
S224. to unblock fingerprint image and the smoothing filtering process of checking fingerprint image;
S225. binary conversion treatment is carried out to unblock fingerprint image and checking fingerprint image;
S226. thinning processing is carried out to unblock fingerprint image and checking fingerprint image.
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| CN105912901A (en) * | 2016-04-06 | 2016-08-31 | 深圳市金立通信设备有限公司 | Fingerprint authentication method and terminal |
| CN106056081A (en) * | 2016-05-30 | 2016-10-26 | 广东欧珀移动通信有限公司 | Unlocking control method and terminal equipment |
| CN106155787A (en) * | 2016-06-28 | 2016-11-23 | 宇龙计算机通信科技(深圳)有限公司 | The management method of application program, the managing device of application program and terminal |
| CN106203151A (en) * | 2016-06-21 | 2016-12-07 | 广东欧珀移动通信有限公司 | A kind of method opening file and terminal unit |
| CN106355141A (en) * | 2016-08-24 | 2017-01-25 | 上海传英信息技术有限公司 | Portable electronic device and operation method thereof |
| CN106529481A (en) * | 2016-11-11 | 2017-03-22 | 努比亚技术有限公司 | Fingerprint identification parameter configuration device and method |
| CN106778160A (en) * | 2016-11-28 | 2017-05-31 | 上海摩软通讯技术有限公司 | Data item display methods and device |
| CN107480491A (en) * | 2017-07-19 | 2017-12-15 | 广东欧珀移动通信有限公司 | Information processing method and related product |
| CN107609392A (en) * | 2017-08-02 | 2018-01-19 | 宇龙计算机通信科技(深圳)有限公司 | A kind of application program encryption method, device and mobile terminal |
| CN108182375A (en) * | 2016-12-08 | 2018-06-19 | 广东精点数据科技股份有限公司 | A kind of fingerprint recognition system based on mobile-phone payment |
| CN108292335A (en) * | 2015-12-24 | 2018-07-17 | 维普公司 | Biometric device |
| CN111309276A (en) * | 2020-02-25 | 2020-06-19 | Oppo广东移动通信有限公司 | Information display method and related product |
| CN113129480A (en) * | 2019-12-31 | 2021-07-16 | 广州海英智慧家居科技有限公司 | Fingerprint lock control method for Internet of things |
| CN114499994A (en) * | 2021-12-30 | 2022-05-13 | 科大讯飞股份有限公司 | Device fingerprint identification method and device, electronic device and medium |
| CN114499994B (en) * | 2021-12-30 | 2024-06-04 | 科大讯飞股份有限公司 | Equipment fingerprint identification method and device, electronic equipment and medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108292335A (en) * | 2015-12-24 | 2018-07-17 | 维普公司 | Biometric device |
| CN105912901A (en) * | 2016-04-06 | 2016-08-31 | 深圳市金立通信设备有限公司 | Fingerprint authentication method and terminal |
| CN106056081A (en) * | 2016-05-30 | 2016-10-26 | 广东欧珀移动通信有限公司 | Unlocking control method and terminal equipment |
| US10423816B2 (en) | 2016-05-30 | 2019-09-24 | Guangdong Oppo Mobile Telecommunications Corp., Ltd. | Method for controlling unlocking and terminal device |
| CN106203151A (en) * | 2016-06-21 | 2016-12-07 | 广东欧珀移动通信有限公司 | A kind of method opening file and terminal unit |
| CN106203151B (en) * | 2016-06-21 | 2019-02-12 | Oppo广东移动通信有限公司 | A kind of method and terminal device for opening file |
| CN106155787A (en) * | 2016-06-28 | 2016-11-23 | 宇龙计算机通信科技(深圳)有限公司 | The management method of application program, the managing device of application program and terminal |
| CN106355141A (en) * | 2016-08-24 | 2017-01-25 | 上海传英信息技术有限公司 | Portable electronic device and operation method thereof |
| CN106529481A (en) * | 2016-11-11 | 2017-03-22 | 努比亚技术有限公司 | Fingerprint identification parameter configuration device and method |
| CN106778160A (en) * | 2016-11-28 | 2017-05-31 | 上海摩软通讯技术有限公司 | Data item display methods and device |
| CN108182375A (en) * | 2016-12-08 | 2018-06-19 | 广东精点数据科技股份有限公司 | A kind of fingerprint recognition system based on mobile-phone payment |
| CN107480491A (en) * | 2017-07-19 | 2017-12-15 | 广东欧珀移动通信有限公司 | Information processing method and related product |
| CN107609392A (en) * | 2017-08-02 | 2018-01-19 | 宇龙计算机通信科技(深圳)有限公司 | A kind of application program encryption method, device and mobile terminal |
| CN113129480A (en) * | 2019-12-31 | 2021-07-16 | 广州海英智慧家居科技有限公司 | Fingerprint lock control method for Internet of things |
| CN111309276A (en) * | 2020-02-25 | 2020-06-19 | Oppo广东移动通信有限公司 | Information display method and related product |
| CN111309276B (en) * | 2020-02-25 | 2023-08-22 | Oppo广东移动通信有限公司 | Information display method and related product |
| CN114499994A (en) * | 2021-12-30 | 2022-05-13 | 科大讯飞股份有限公司 | Device fingerprint identification method and device, electronic device and medium |
| CN114499994B (en) * | 2021-12-30 | 2024-06-04 | 科大讯飞股份有限公司 | Equipment fingerprint identification method and device, electronic equipment and medium |
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Application publication date: 20150909 |