Finger vein recognition method based on fusion of local features and global features
A technology of local features and global features, applied in the field of finger vein recognition, can solve problems such as the impact of recognition accuracy, and achieve the effects of reliable recognition results, overcoming limitations, and high use value
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Embodiment 1
[0023] A finger vein recognition method that integrates local features and global features. Firstly, preprocessing operations such as finger area extraction and binarization are performed on the read finger vein images; The feature recognition module realizes the matching of local features within a certain angle and radius; the global feature recognition module for two-way two-dimensional principal component analysis can better display the two-dimensional image data set as a whole, and use it for vein Image recognition realizes the matching of global features; finally, weights are designed according to the correct recognition rates of the two recognition methods, and the results of the two classifiers are fused at the decision level, and the fused result is taken as the final recognition result.
Embodiment 2
[0025] According to the finger vein recognition method for fusing local features and global features described in Embodiment 1, the flexible matching local feature recognition module,
[0026] (1) First, extract the finger area, binarize, and thin the original finger vein image, and then extract the feature points of the thinned image, that is, the endpoint and the intersection point;
[0027] (2) Read in template image feature points and feature points of the image to be matched ,judge with Is it satisfied , if not established, repeat this step and read in another pair of feature points, otherwise turn to step (3), until all the details point pairs are compared, go to the last step;
[0028] (3) Accumulate the number of similar feature points;
[0029] (4) According to the following similarity calculation formula, the matching similarity between the template image and the feature point set of the image to be matched is obtained, and compared with the qualified thres...
Embodiment 3
[0033] According to the finger vein recognition method of fusing local features and global features described in Embodiment 1 or 2, the decision-making level fusion, after obtaining the recognition method based on flexible matching and the finger vein recognition method based on two-dimensional two-dimensional principal component analysis After the correct recognition rate and the recognition result, the weights are designed according to the correct recognition rate of the two recognition methods, so as to determine the proportion of the recognition results of the two recognition methods in the final fusion result; after obtaining the global feature method and Correct recognition rate of local feature method with and the recognition results of these two recognition systems with Finally, the final recognition result is obtained by linear fitting; among them, with The value of is 1 or 0, 1 indicates that the system verification is successful, and 0 indicates that the v...
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