37 results about "Automated fingerprint identification" patented technology

A method and system for performing automated biological identification. The system including a preprocessing module with a histogram transform for locally and globally enhancing biological data such as fingerprints. An enhancement module with a fast smoothing and enhancement function. A feature extraction module with a fingerprint oriented thinning function. A matching module with a resolution-enhanced Hough transform function for fingerprint registration and matching score function.

The automatic fingerprint distinguishing method based on template learning includes the following steps: registering fingerprint figure and recording the fingerprint template and characteristic information of the fingerprint figure to be matched; distinguishing fingerprint figure to judge whether the characteristic information of the fingerprint figure is the same as that of some template information in the system data base; feeding back detail information in fingerprint figure via knowledge rule to perfect corresponding reliable detail points in templates. The present invention classifies detail points of fingerprint templates, records the kernel of classes, interval and other information and has one coarse matching link before common matching. The present invention can extract and repair the characteristic information of multiple templates, raise the distinction effect and performance of automatic fingerprint distinguishing system, and has important application in biological distinction.

The invention discloses a living fingerprint verifying method based on a thin-plate spline deformable model, which collects and preprocesses the fingerprint sequence of a finger for verifying, registers the fingerprints before and after deformation, selects corresponding minutiae point pair to serve as the criterion point pair for estimating the thin-plate spline model, employs improved thin-plate spline model to describe deformation of fingerprints, computes the deformable energy of the fingerprint for verifying in each direction on the basis of model parameter to an overall bending energy vector, trains respectively on a true and a false fingerprint deformation base, obtains space distribution of the bending energy vector, respectively computes similarity from the bending energy vector for measuring to an eigen fuzzy set of true and false bending energies, and selects proper threshold value to obtain the verifying result. The invention can identify false fingerprint from the living fingerprint, effectively realizes living fingerprint verification in real-time, increases safety of automatic fingerprint verifying systems, enlarges the application range of automatic fingerprint verifying systems and has important application value in the field of biological character identification.

This invention relates to an identifying method for deformed fingerprints based on local triangle structure character set, on the basis of the character that relative deformation of fingerprint image is limit in local regions, which expresses fingerprints with a fuzzy character-local triangle structure character sets to convert the computation to integral similarity among fingerprints to similarity balance among character sets, first of all, which puts forward a fuzzy measurement method of similarity between two triangle structures then further makes up of a character vector composed of local similarities of all triangle structures then to map the pair of similarity vectors to a normalized number in the region of [0, 1] to quantize the integral similarity among fingerprint images to further get the matched result.

This invention relates to an automatic fingerprint identification and sorting system and method, which divides the fingerprint into six kinds: arch, sharp arch, left rotation, right rotation and whirl and singular and is based on the number of the fingerprint singular points and surround ridge line direction. The method comprises the following steps: to divide the fingerprint images into front area and back area through the dividing program; to form a block field image to the print image in the front area; to determine the position and direction of the singular points by use of block direction field; to divide the print into six kinds according to the number and direction of the singular points and the pre-set rules.

The invention discloses a fingerprint image quality evaluation method based on main component analysis. The method comprises the following steps of: blocking an input fingerprint image; acquiring field pixel information of each pixel point in the image blocks, and forming a block sample matrix; acquiring a projection matrix and a characteristic value vector of the block sample matrix by a main component analyzing method; calculating characteristics for image block quality judgment from the projection matrix and the characteristic value vector; obtaining the local block quality of the image blocks by the multiplication rule; and obtaining the overall quality of the input fingerprint image through the combination of block Harris strength. The method is simple; a result is intuitive; the quality of the input fingerprint image can be accurately and quantitatively reflected by the method; and the high performance of automatic fingerprint identification technology is ensured by the method.

The invention discloses a substructure-based twins similar fingerprint recognition system and a method. The recognition system comprises a preprocessor, a substructure template device, and a detailed point substructure matching device. The method comprises the following steps: preprocessing a collected fingerprint image and obtaining a refined image of the fingerprint; picking up crest line tip ends and forked detailed points P, constructing substructures based on the aggregate of the picked detailed points P, and generating a fingerprint template through assembling the substructures of the fingerprint; comparing the inputted fingerprint substructure template with fingerprint templates in a database, calculating the differentia of relative position and orientation parameters between substructures and judging whether two fingerprints are matched with each other. The invention adopts the detailed point substructures, thereby not only remarkably improving the twins similar fingerprint recognition performance of the automatic fingerprint recognition system, but also solving the problem of reduced recognition rate due to similar global features of two fingerprints and widening the application of the fingerprint recognition system in the special group of twins.

The present invention discloses a rapid fingerprint identification method based on the singular point topology structure, and the rapid fingerprint identification method can fast process and identify the fingerprint images in the automated fingerprint identification system by using singular point topology structure in fingerprints. The present invention classifies the fingerprint database according to the classification property and position stability of the singular point in fingerprint images, and selects the most reliable singular point as a reference point to build the singular point topology structure of fingerprints and a module to identify; the present invention firstly detects the authenticity of singular points in a fingerprint image, and then classifies the database according to the relative position of singular points to build a topology structure adjacent to the singular point; and the topology structure can be used to build the fingerprint module to speed up the comparison process of the fingerprints; the rapid matching of fingerprints in the automated fingerprint identification system is a difficulty of the fingerprint recognition technology; the rapid fingerprint identification method, on one hand, can guarantee the recognition performance, on the other hand, can significantly improve the recognition speed of the automated fingerprint identification system, and can widen the scope of application; moreover, the method reforms the prior system slightly.

The invention relates to a fingerprint identification method and a system thereof, relates to a fingerprint image enhancement method and discloses an image enhancement method in an automatic fingerprint identification technology. The method is characterized by: firstly, constructing a two-dimensional sine filter which has a consistent with a fingerprint; then, using a two-dimensional Gaussian function to carry out modulation on the two-dimensional sine filter so as to obtain a Gaussian modulation two-dimensional sine filter; and carrying out correction on the Gaussian modulation two-dimensional sine filter, constructing the filter which accords with an actual need of fingerprint image processing; using a frequency parameter and a direction parameter of each fingerprint image area to construct an appropriate enhancement template of the Gaussian modulation two-dimensional sine filter; finally carrying out convolution operation on the corresponding Gaussian modulation two-dimensional sine filter template and the corresponding fingerprint image area, carrying out enhancement processing on the fingerprint image, and carrying out normalization processing on an enhancement result so as to obtain the final enhancement fingerprint image.

The invention discloses a fingerprint direction field calculation method based on an improved partial differential model, and belongs to the technical field of automatic fingerprint recognition. The fingerprint direction field calculation method mainly comprises two steps: I, solving an initial direction field of fingerprint by using a basic gradient algorithm; II, smoothing the initial direction field by using the improved partial differential model. The fingerprint direction field calculation method mainly aims to improve holding items of a conventional partial differential model, that is, firstly, the situation that the initial direction field in the conventional model is taken as holding standard is improved into the situation that the direction field of previous iteration is taken as the holding standard, and secondly, a static capture singular point function in the conventional model is improved to be a dynamic capture singular point function. By adopting the fingerprint direction field calculation method disclosed by the invention, noise areas and singular point areas can be effectively distinguished, the algorithm is relatively reasonable, the iteration times can be effectively reduced, the algorithm efficiency can be improved, and the direction field can be relatively accurately calculated.

The invention discloses an fingerprint image direction field calculation method in an automatic fingerprint identification system. The fingerprint image direction field calculation method adopts a GVF-model based method and comprises the following steps: (1) inputting a fingerprint image; (2) calculating the gradient distribution, the quality score and the crack mask of the input fingerprint image; (3) judging the fingerprint quality, carrying out the step (4) if the fingerprint quality is bad, or carrying out the step (5) if the fingerprint quality is not bad; (4) actuating the crack mask and the initial GVF (gradient vector flow) field V0, and omitting the noise data in a crack region; (5) diffusing the initial GVF field V0 rapidly and smoothly, and taking the diffused GVF field as the Vcoarse; (6) calculating the distribution theta corse (x, y) of the direction field of the fingerprint by using the Vcoarse, detecting a singular point, and obtaining a singular region mask MSingulsr; (7) mending the Vcoarse of a singular region by using a GGVF (general gradient vector flow) model to obtain a final GVF field VFine; and (8) calculating the final direction field theta (x, y). The method overcomes the detects of poor low-quality background region image calculation effect of the prior art and achieves good low-quality fingerprint image calculation effect and the good result of obtaining the direction filed in the fingerprint background region.

The present invention belongs to the digital image processing technical field and discloses a selective extension-based fingerprint image matching method. According to the method, small fingerprint image matching is carried out by using small node and directional field information; fingerprint blocks with small nodes and fingerprint blocks without small nodes are considered differently through extending the functions of directional fields, so that feature extraction is realized; and matching scores are fused, so that the extracted features of small fingerprints can be fully applied. With the method adopted, more comprehensive feature extraction can be realized. Since the matching scores are fused, the extracted features of the small fingerprints can be fully applied, and accuracy can be improved. The method can accurately match the small nodes of fingerprints and can be used in an automatic fingerprint identification system.

A method for automated fingerprint identification and special purpose programmed computer for carrying out the method are disclosed. The method and system comprise identifying a scar region in a set of pixels in a fingerprint image by using a second order Gaussian derivative filter parameterized using standard deviation, wherein the scar region has a width greater that the width of a regular ridge or a valley of separation between ridges; wherein a boundary, intensity, and flow direction of each pixel is calculated; each pixel being connected to a next adjacent pixel using flow co-ordinates and flow directions; wherein the Gaussian derivative filter has an output and the output is thresholded to create an output mask with value=1 at the scar regions and value=0 outside the scar regions; and changing the intensity of pixels in the identified scar region with the intensity of the nearest boundary pixel until the intensities of all the pixels in the scar region are changed to the intensity of their flow direction identified boundary pixels.

The invention relates to a fingerprint image frame line deletion method, which pertains to the digital image processing and fingerprint identification technical fields. The filtering method is characterized in that: an image with the size of m multiplied by n is firstly carried out the band-stop filter pre-treatment, the image after the pre-treatment is carried out the binary processing, two windows with the size of m multiplied by 9 and 9 multiplied by n are used for scanning the whole image along the longitudinal direction and the transverse direction, the minimum value of the sums of rows of pixels is calculated within the window field with the size of m multiplied by 9, the minimum value of the sums of lines of pixels is calculated within the window field with the size of 9 multiplied by n, the filling of the image is carried out according to the values and the deletion of the image frame lines is completed. The deletion method has the advantages that: the deletion method is applicable to the removal of an interference which is generally existed in an automatic fingerprint identification system, thus allowing the automatic fingerprint identification to be more accurate.

The invention relates to a fingerprint feature construction method based on minutiae, and belongs to the technical field of the automatic fingerprint recognition. The method is used for obtaining minutia pairs in the fingerprint matching process and includes the first step of preprocessing a fingerprint image, the second step of establishing a right-angle coordinate system called RCS and determining the directions of the coordinate system, the third step of defining and finding the effectively minutiae belonging to the RCS coordinate system, and the fourth step of calculating the number of regression lines related to the effective minutiae and conducting inspection. The method has the advantages that by means of the features, the features of the minutiae and the regression line information related to the minutiae are combined, and the reliability of the extracted features is improved; the directions of the coordinate system are determined, and the anti-rotation performance of the algorithm can be effectively improved; the method for calculating the number of the regression lines is described in details and achieved, and the inspection shows that the calculation result is quite accurate; only the features of the minutiae belonging to the RCS coordinate system are extracted, the number of the extracted features of the minutiae is reduced, and the running efficiency of the algorithm is improved.