CN119203104A - Application startup method and system based on fingerprint recognition - Google Patents
Application startup method and system based on fingerprint recognition Download PDFInfo
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- CN119203104A CN119203104A CN202411709613.2A CN202411709613A CN119203104A CN 119203104 A CN119203104 A CN 119203104A CN 202411709613 A CN202411709613 A CN 202411709613A CN 119203104 A CN119203104 A CN 119203104A
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/10—Protecting distributed programs or content, e.g. vending or licensing of copyrighted material ; Digital rights management [DRM]
- G06F21/16—Program or content traceability, e.g. by watermarking
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/28—Quantising the image, e.g. histogram thresholding for discrimination between background and foreground patterns
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/12—Fingerprints or palmprints
- G06V40/1347—Preprocessing; Feature extraction
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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
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Abstract
The application provides an application starting method and system based on fingerprint identification, wherein the method comprises the steps of obtaining fingerprint images of related users, carrying out gray level processing on the fingerprint images to obtain gray level images, preprocessing the gray level images to obtain preprocessed images, extracting corresponding required image features from the preprocessed images, carrying out one-by-one matching on the required image features and a plurality of watermark images in a prerecorded fingerprint library through intelligent contracts, associating at least one software application with the watermark images, storing corresponding association relations in a blockchain, displaying current software applications associated with the watermark images successfully matched when the matching is successful, selecting target software applications from the current software applications based on requirements, and starting and automatically logging in the target software applications. The method and the device are beneficial to improving the flexibility of the software application starting operation and the convenience of the software application starting operation.
Description
Technical Field
The invention relates to the technical field of electronic equipment application, in particular to an application starting method and system based on fingerprint identification.
Background
At present, in order to realize login in software, the traditional mode is to input account names and passwords, the mode is inconvenient to input on a touch screen, the password is not safe enough to input in public places, the mode is also to use a mobile phone which is popular at present to scan two-dimension codes to log in, but the mode is required to require computers to be networked, and is influenced by network speed, experience is possibly unstable, the mode is to use an external fingerprint identification module to automatically log in through fingerprints by binding fingerprint and account information, but the mode can cause all login information to be stored in the external fingerprint module, the login information has a binding relation with the corresponding fingerprint module, if the module is replaced or lost, the binding relation between the fingerprints and the account is required to be re-input, the mode is inflexible, and the premise of login is that the corresponding software is required to be found and opened on equipment, so that the mode is often not convenient for public scenes such as a teacher to learn.
Disclosure of Invention
Based on the above, the invention aims to provide an application starting method and system based on fingerprint identification, so as to solve the defects in the prior art.
In order to achieve the above object, the present invention provides an application starting method based on fingerprint identification, the method comprising:
acquiring a fingerprint image of a related user, and carrying out graying treatment on the fingerprint image to obtain a gray image;
preprocessing the gray level image to obtain a preprocessed image;
Extracting corresponding required image features from the preprocessed image, and matching the required image features with a plurality of watermark images in a prerecorded fingerprint library one by one through an intelligent contract, wherein the watermark images are associated with at least one software application, and corresponding association relations are stored in a blockchain;
And when the matching is successful, displaying the current software application associated with the watermark image which is successfully matched, selecting a target software application from the current software applications based on requirements, and starting and automatically logging in the target software application.
Preferably, before the required image features are matched with the watermark images in the prerecorded fingerprint library one by one through the intelligent contract, the method further comprises:
collecting a fingerprint image of a user, acquiring a gray level image corresponding to the fingerprint image, and respectively acquiring pixel values of the fingerprint image and the gray level image;
Calculating an initial pixel value based on the pixel values of the fingerprint image and the gray level image through an embedded intervention algorithm, and obtaining an initial watermark image based on the initial pixel value;
Acquiring pixel values of the initial watermark image, calculating the latest pixel value based on the pixel values of the initial watermark image and the fingerprint image, and acquiring the watermark image corresponding to the fingerprint image based on the latest pixel value;
And storing the fingerprint image and the corresponding watermark image into a block chain.
Preferably, the expression of the embedded intervention algorithm is as follows:
Wherein, For the red component value of the initial watermark image,For the green component value of the initial watermark image,For the blue component value of the initial watermark image,For the red component value of the fingerprint image,For the green component value of the fingerprint image,For the blue component value of the fingerprint image,For the red component value of the gray scale image,For the green component value of the gray scale image,For the blue component value of the gray scale image,For embedding intervention coefficients.
Preferably, the step of preprocessing the gray-scale image includes:
performing image enhancement processing on the gray level image to obtain an enhanced fingerprint image;
Performing binarization processing on the enhanced fingerprint image to obtain a binary image;
and carrying out refinement treatment on the binary image to obtain a preprocessed image.
Preferably, the step of extracting the corresponding required image features from the preprocessed image comprises:
extracting an original detail characteristic point set from the preprocessed image;
analyzing the original detail characteristic point set to obtain a distribution rule of characteristic points of the fingerprint image;
And screening the pseudo feature points based on the line direction of the fingerprint image and the distribution rule of the feature points to obtain real feature points, wherein the real feature points are the required image features.
Preferably, after the required image features are matched with the watermark images in the prerecorded fingerprint library one by one through the intelligent contract, the method comprises the following steps:
and when the matching fails, judging that the corresponding user matched with the fingerprint image is an illegal user, and restoring the display interface to an initial state.
Preferably, before the selecting, based on the requirement, the target software application from the current software applications, the method further includes:
And logging in the software application in advance, and automatically storing corresponding account information.
In order to achieve the above object, the present invention further provides an application starting system based on fingerprint identification, for implementing the application starting method based on fingerprint identification described in the above, where the system includes:
The acquisition module is used for acquiring a fingerprint image of a related user and carrying out graying treatment on the fingerprint image so as to obtain a gray image;
The preprocessing module is used for preprocessing the gray level image to obtain a preprocessed image;
The matching module is used for extracting corresponding required image features from the preprocessed image, and matching the required image features with a plurality of watermark images in a prerecorded fingerprint library one by one, wherein the watermark images are associated with at least one software application, and corresponding association relations are stored in a blockchain;
And the starting module is used for displaying the current software application associated with the watermark image which is successfully matched when the matching is successful, selecting a target software application from the current software applications based on requirements, and starting and automatically logging in the target software application.
Preferably, before the matching module, the system further includes:
The acquisition module is used for acquiring a fingerprint image of a user, acquiring a gray image corresponding to the fingerprint image, and respectively acquiring pixel values of the fingerprint image and the gray image;
The first calculation module is used for calculating an initial pixel value based on the pixel values of the fingerprint image and the gray level image through an embedded intervention algorithm and obtaining an initial watermark image based on the initial pixel value;
The second calculation module is used for acquiring pixel values of the initial watermark image, calculating the latest pixel value based on the pixel values of the initial watermark image and the fingerprint image, and acquiring the watermark image corresponding to the fingerprint image based on the latest pixel value;
and the storage module is used for storing the fingerprint image and the corresponding watermark image into a blockchain.
Preferably, the expression of the embedded intervention algorithm is as follows:
Wherein, For the red component value of the initial watermark image,For the green component value of the initial watermark image,For the blue component value of the initial watermark image,For the red component value of the fingerprint image,For the green component value of the fingerprint image,For the blue component value of the fingerprint image,For the red component value of the gray scale image,For the green component value of the gray scale image,For the blue component value of the gray scale image,For embedding intervention coefficients.
The fingerprint module is used for acquiring a corresponding gray level image by carrying out gray level processing on a fingerprint image of a related user, then carrying out preprocessing on the gray level image to acquire a preprocessed image, extracting corresponding required image characteristics from the preprocessed image, carrying out one-by-one matching on the required image characteristics and a plurality of watermark images in a prerecorded fingerprint library through an intelligent contract, associating the watermark images with software applications, storing association relations in a blockchain, displaying the current software application associated with the successfully matched watermark images when the matching is successful, selecting a target software application from the current software application based on requirements, and then starting and automatically logging in the target software application.
Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
FIG. 1 is a flowchart of an application start method based on fingerprint identification according to a first embodiment of the present invention;
fig. 2 is a block diagram of an application starting system based on fingerprint recognition according to a second embodiment of the present invention.
The invention will be further described in the following detailed description in conjunction with the above-described figures.
Detailed Description
The present application will be described and illustrated with reference to the accompanying drawings and examples in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application. All other embodiments, which can be made by a person of ordinary skill in the art based on the embodiments provided by the present application without making any inventive effort, are intended to fall within the scope of the present application.
It is apparent that the drawings in the following description are only some examples or embodiments of the present application, and it is possible for those of ordinary skill in the art to apply the present application to other similar situations according to these drawings without inventive effort. Moreover, it should be appreciated that while such a development effort might be complex and lengthy, it would nevertheless be a routine undertaking of design, fabrication, or manufacture for those of ordinary skill having the benefit of this disclosure, and thus should not be construed as having the benefit of this disclosure.
Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is to be expressly and implicitly understood by those of ordinary skill in the art that the described embodiments of the application can be combined with other embodiments without conflict.
Unless defined otherwise, technical or scientific terms used herein should be given the ordinary meaning as understood by one of ordinary skill in the art to which this application belongs. The terms "a," "an," "the," and similar referents in the context of the application are not to be construed as limiting the quantity, but rather as singular or plural. The terms "comprises," "comprising," "includes," "including," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or modules (elements) is not limited to only those steps or elements but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus. The terms "connected," "coupled," and the like in connection with the present application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The term "plurality" as used herein means two or more. "and/or" describes the association relationship of the association object, and indicates that three relationships may exist, for example, "a and/or B" may indicate that a exists alone, a and B exist simultaneously, and B exists alone. The character "/" generally indicates that the context-dependent object is an "or" relationship. The terms "first," "second," "third," and the like, as used herein, are merely distinguishing between similar objects and not representing a particular ordering of objects.
Referring to fig. 1, a flowchart of an application starting method based on fingerprint identification in a first embodiment of the present invention is shown, and the application starting method based on fingerprint identification includes the following steps:
Step S101, acquiring a fingerprint image of a related user, and carrying out graying treatment on the fingerprint image to obtain a gray image;
if the fingerprint image is a color image, the gray value of the gray image needs to be calculated according to the following gray pixel calculation formula, and then the subsequent processing is performed.
It should be noted that the gray pixel calculation formula is as follows:
Wherein, For the red component value of the fingerprint image,For the green component value of the fingerprint image,For the blue component value of the fingerprint image,Is the gray value of the gray image.
Step S102, preprocessing the gray level image to obtain a preprocessed image;
And sequentially carrying out noise removal, binarization and refinement treatment on the gray level image to obtain a preprocessed image.
Step S103, extracting corresponding required image features from the preprocessed image, and matching the required image features with a plurality of watermark images in a prerecorded fingerprint library one by one through an intelligent contract, wherein the watermark images are associated with at least one software application, and corresponding association relations are stored in a blockchain;
The watermark image is obtained through corresponding processing of the fingerprint image, the fingerprint image corresponds to one watermark image, the watermark image is associated with at least one software application through an intelligent contract, the association between the watermark image and the software application can be ensured not to be tampered at will, the random replacement of a fingerprint module can be realized and the influence is not caused, and the association relation between the watermark image and the software application is stored in a blockchain.
And step S104, when the matching is successful, displaying the current software application associated with the watermark image which is successfully matched, selecting a target software application from the current software applications based on requirements, and starting and automatically logging in the target software application.
Before matching, each software application logs in advance and stores corresponding account information so that when the target software application is selected, the target software application can be started and automatically logged in.
Through the steps, the fingerprint images of related users are subjected to graying treatment to obtain corresponding gray images, then the gray images are preprocessed to obtain preprocessed images, corresponding image features are extracted from the preprocessed images, the image features are matched with a plurality of watermark images in a prerecorded fingerprint library one by one through intelligent contracts, the watermark images are associated with software applications, association relations are stored in a blockchain, when matching is successful, the current software application associated with the successfully matched watermark images is displayed, a target software application is selected from the current software application based on requirements, and then the target software application is started and automatically logged in.
In some embodiments, before the matching the required image features with the watermark images in the prerecorded fingerprint library one by one, the method further includes:
collecting a fingerprint image of a user, acquiring a gray level image corresponding to the fingerprint image, and respectively acquiring pixel values of the fingerprint image and the gray level image;
Wherein red, green and blue component values of the fingerprint image and the gray scale image need to be acquired, respectively.
Calculating an initial pixel value based on the pixel values of the fingerprint image and the gray level image through an embedded intervention algorithm, and obtaining an initial watermark image based on the initial pixel value;
The red component value, the green component value and the blue component value of the initial watermark image are calculated through the embedding intervention algorithm, namely, an initial pixel value is calculated, and at the moment, the initial watermark image is an image embedded with a watermark.
It should be noted that the expression of the embedded intervention algorithm is as follows:
Wherein, For the red component value of the initial watermark image,For the green component value of the initial watermark image,For the blue component value of the initial watermark image,For the red component value of the fingerprint image,For the green component value of the fingerprint image,For the blue component value of the fingerprint image,For the red component value of the gray scale image,For the green component value of the gray scale image,For the blue component value of the gray scale image,For embedding intervention coefficients.
Acquiring pixel values of the initial watermark image, calculating the latest pixel value based on the pixel values of the initial watermark image and the fingerprint image, and acquiring the watermark image corresponding to the fingerprint image based on the latest pixel value;
The process of calculating the latest pixel value is an inverse process of the process of calculating the initial pixel value, and the process of calculating the latest pixel value is specifically to calculate a difference value between the pixel value of the initial watermark image and the pixel value of the fingerprint image, wherein the difference value is a final pixel value of the watermark image, and the pixel value comprises a red component value, a green component value and a blue component value.
It should be noted that, the formula for calculating the latest pixel value is as follows:
Wherein, For the red component value of the watermark image,For the green component value of the watermark image,Is the blue component value of the watermark image.
And storing the fingerprint image and the corresponding watermark image into a block chain.
In some of these embodiments, the step of preprocessing the grayscale image includes:
performing image enhancement processing on the gray level image to obtain an enhanced fingerprint image;
The gray level image is divided into a plurality of area blocks, then the local direction of the ridge lines and the valley lines of each area block are obtained through the frequency domain processing after wavelet transformation, and the definition of the ridge lines and the valley lines of the fingerprint image is obtained based on the local direction of the ridge lines, so that the enhanced fingerprint image is obtained.
Performing binarization processing on the enhanced fingerprint image to obtain a binary image;
The binarization processing is performed to change the 256-level enhanced fingerprint image into a binary image, specifically, the binarization processing is performed on the enhanced fingerprint image by a thresholding method.
And carrying out refinement treatment on the binary image to obtain a preprocessed image.
In some of these embodiments, the step of extracting the corresponding desired image features from the preprocessed image comprises:
extracting an original detail characteristic point set from the preprocessed image;
analyzing the original detail characteristic point set to obtain a distribution rule of characteristic points of the fingerprint image;
And screening the pseudo feature points based on the line direction of the fingerprint image and the distribution rule of the feature points to obtain real feature points, wherein the real feature points are the required image features.
Because of various interference reasons, such as artificial noise introduced by preprocessing, or fracture and adhesion of lines which cannot be eliminated, characteristic points are obtained in the image characteristic extraction process, and part of pseudo characteristic points interfere with the accuracy of subsequent fingerprint matching, therefore, inferior pseudo characteristic points need to be screened out, real characteristic points are stored, and the real characteristic points are used as the required image characteristics.
In some embodiments, after the matching the required image features to the watermark images in the pre-recorded fingerprint library one by one, the method further comprises:
and when the matching fails, judging that the corresponding user matched with the fingerprint image is an illegal user, and restoring the display interface to an initial state.
In some of these embodiments, before the selecting the target software application from the current software applications based on the requirements, the method further comprises:
And logging in the software application in advance, and automatically storing corresponding account information.
It should be noted that the steps illustrated in the above-described flow or flow diagrams of the figures may be performed in a computer system, such as a set of computer-executable instructions, and that, although a logical order is illustrated in the flow diagrams, in some cases, the steps illustrated or described may be performed in an order other than that illustrated herein.
The second embodiment of the present application further provides an application starting system based on fingerprint identification, which is used for implementing the first embodiment and the preferred embodiment, and is not described in detail. As used below, the terms "module," "unit," "sub-unit," and the like may be a combination of software and/or hardware that implements a predetermined function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.
Fig. 2 is a fingerprint recognition-based application starting system according to a second embodiment of the present application, as shown in fig. 2, the system includes:
the acquisition module 10 is used for acquiring a fingerprint image of a related user and carrying out graying treatment on the fingerprint image so as to obtain a gray image;
a preprocessing module 20, configured to preprocess the gray scale image to obtain a preprocessed image;
The matching module 30 is configured to extract corresponding required image features from the preprocessed image, and match the required image features with a plurality of watermark images in a prerecorded fingerprint library one by one through an intelligent contract, where the watermark images are associated with at least one software application, and the corresponding association relationships are stored in a blockchain;
And the starting module 40 is used for displaying the current software application associated with the watermark image which is successfully matched when the matching is successful, selecting a target software application from the current software applications based on requirements, and starting and automatically logging in the target software application.
In the implementation, the corresponding gray level image is obtained by carrying out gray level processing on the fingerprint image of the related user, then the gray level image is preprocessed to obtain the preprocessed image, the corresponding required image characteristics are extracted from the preprocessed image, the required image characteristics are matched with a plurality of watermark images in a prerecorded fingerprint library one by one through an intelligent contract, the watermark images are associated with the software application, the association relation is stored in a blockchain, when the matching is successful, the current software application associated with the successfully matched watermark image is displayed, the target software application is selected from the current software application based on the requirement, and then the target software application is started and automatically logged in.
In some of these embodiments, prior to the matching module 30, the system further comprises:
The acquisition module is used for acquiring a fingerprint image of a user, acquiring a gray image corresponding to the fingerprint image, and respectively acquiring pixel values of the fingerprint image and the gray image;
The first calculation module is used for calculating an initial pixel value based on the pixel values of the fingerprint image and the gray level image through an embedded intervention algorithm and obtaining an initial watermark image based on the initial pixel value;
The second calculation module is used for acquiring pixel values of the initial watermark image, calculating the latest pixel value based on the pixel values of the initial watermark image and the fingerprint image, and acquiring the watermark image corresponding to the fingerprint image based on the latest pixel value;
and the storage module is used for storing the fingerprint image and the corresponding watermark image into a blockchain.
In some of these embodiments, the expression of the embedded intervention algorithm is as follows:
Wherein, For the red component value of the initial watermark image,For the green component value of the initial watermark image,For the blue component value of the initial watermark image,For the red component value of the fingerprint image,For the green component value of the fingerprint image,For the blue component value of the fingerprint image,For the red component value of the gray scale image,For the green component value of the gray scale image,For the blue component value of the gray scale image,For embedding intervention coefficients.
In some of these embodiments, the preprocessing module 20 includes:
the enhancement unit is used for carrying out image enhancement processing on the gray level image to obtain an enhanced fingerprint image;
the binarization unit is used for carrying out binarization processing on the enhanced fingerprint image to obtain a binary image;
and the thinning unit is used for carrying out thinning treatment on the binary image to obtain a preprocessed image.
In some of these embodiments, the matching module 30 includes:
An extracting unit, configured to extract an original minutiae point set from the preprocessed image;
The analysis unit is used for analyzing the original detail characteristic point set to obtain a distribution rule of characteristic points of the fingerprint image;
And the screening unit is used for screening the pseudo feature points based on the line direction of the fingerprint image and the distribution rule of the feature points to obtain real feature points, wherein the real feature points are the features of the required image.
In some of these embodiments, after the matching module 30, the system further comprises:
And the recovery module is used for judging that the user matched with the corresponding fingerprint image is an illegal user when the matching fails, and recovering the display interface to an initial state.
In some of these embodiments, prior to the start-up module 40, the system further comprises:
and the storage module is used for logging in the software application in advance and automatically storing corresponding account information.
The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of the application should be assessed as that of the appended claims.
Claims (10)
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