Research On Iris Recognition Method Based On Image Matching

It needs so many high information alternations in so many fields in this high informational society which makes the identify verification of greater and greater importance. The development of biometrics provides a more ideal way to achieve this. Iris, as an important feature to identification, has a higher accuracy in many biometric methods.When the eyes are in natural opening state, images sampled are easily disturbed by the eyelid, eyelash and reflected light spot, and in the paper, it analyzes the relationship between useful iris regions that are not disturbed and its corresponding recognition results. It divides the useful region twice and effectively suppresses the rotate distortion when the image was taken. Experiments show that this method is fast and can be used into the personal identification.Many factors, especially illumination will bring prodigious disturb to certain feature in the image taken. To get more representative iris features, an algorithm based on multi-feature fuzzy inference was proposed. Three features, local feature point, local texture direction and changes between brightness and darkness of local texture are extracted through the gray-scale of iris images, which can depict the feature space of texture more fully and overcome the limitation of most previous algorithms which extract only susceptible single feature. Then patterns are categorized by the designed fuzzy inference regulation. Experiments demonstrate that many kinds of features can represent the variation details in the iris patterns properly. The design of this piecewise linear classifier enhances the ability of linear classification of the algorithm and the correctness is improved and the algorithm wins predominant recognition performance.As eyelid and eyelashes are likely to disturb iris texture, the extent cannot be predicted before acquiring iris image. Some fluky and unfixed features are caused by the yawp in feature templates, which make iris classification false rate increase. In order to resolve this problem, a iris recognition algorithm based on multiple region combination is proposed in this paper, iris image that is not liable to be disturbed relatively is separated into four subarea, then the four similarities of corresponding subarea are calculated in two image, features of the closest subarea are considered as the judgment that is used to carry out classification. It overcomes previous limitation brought by selecting only a fixed position to extract features. Results show that proposed means achieves quite high accuracy, which is efficient for boosting up adaptability to image quality and improving iris recognition performance.