Researching And Realization Of Iris Recognition

Biological recognition technology of the21st century, Including: fingerprint recognition, iris recognition, gesture recognition, voice recognition, face recognition and so on. However, in the biological recognition technology, Iris recognition is known the most convenient and most accurate biometric technologies. Its developing prospect is widely recognized. At present, the iris recognition technology had found wide applications in areas such as security, national defense, communication management and electronic commerce, whose market application prospect is very broad.As a biological recognition, iris recognition has the stability, the uniqueness, the gathering, inviolability and other advantages. And compared with the face recognition and fingerprint recognition, iris recognition has a higher accuracy. However, iris recognition which has many advantages of iris recognition has the key problems to be resolved. For instance, the iris images contain a lot of noise, Iris localization algorithm need to be further improved, and how to effectively extract the characteristic information of the iris of iris recognition. This paper emphatically from the several aspects to study the iris recognition algorithms, and basically reached the expected effect.1Suppressing Eyelash Interference Based on Morphology and Wavelet AnalysisIn order to improve the performance of eyelash interference suppressing algorithm in iris recognition, a new method based on morphology and wavelet analysis was proposed. Considering the image has obvious noise interference, firstly get rid of the noise from image with dilation, and then by using wavelet denoising principle, processing the transformation of different scales of high-frequency detailed images with threshold and handle low-frequency image with reverse sharpen masking. Finally by taking inverse wavelet transform to restore the enhanced image. Comparison of iris location experimental results shows that:the ability of restraining eyelash interference of the proposed algorithm is obviously superior, and achieving the needs of the application.2Iris Location Algorithm Based on Ant Colony and Hough Transform In order to improve the speed and the precision of iris location, iris location algorithm based on ant colony and Hough transform was proposed. In the algorithm, the ants search iris edge by the gradient information of iris edge. And then, the boundary-points of iris are gotten according to the constantly increasing pheromone on the path which ants passed through. At last, we can locate the iris in the original image by Otsu threshold and Hough Transform method. The results of experiments show that the proposed algorithm can locate iris accurately and quickly.3A Method of Iris Recognition based on Local Gray Minimum ValuesFeature matching is a most important step of the iris recognition algorithm, directly determining the success or failure of iris recognition. Because of the characteristics of the iris texture, proposing a method of iris recognition based on local gray minimum values. The method firstly records the position of local gray minimum points in the iris region, compress with the minimum consolidation method, and then extracting features and encoding in the compression iris image. Finally, do "xor" operation between encoding information and template information, get the final recognition results. The experimental results show that: this method has very good recognition performance.