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A non-ideal iris image enhancement algorithm based on local standard deviation was put forward. The algorithm can enhance gray and color iris images with poor contrast. Experiments show that the proposed method can increase the correct acceptance rate and reduce the false rejection rate of iris recognition system, so the algorithm can improve the accuracy of iris recognition system.
Iris recognition system is under a rapid development of biometric systems because of the uniqueness and high reliability of iris. The segmentation of iris is a key step in iris recognition, which has a significant effect on the quality of subsequent feature extraction and matching. The main propose of iris segmentation is to get more iris region and exclude eyelashes, eyelids and other interference...
Iris recognition technology is one of the most promising biological recognition technologies now. In order to ensure the efficiency and accuracy of recognition algorithm, we need to evaluate the quality of iris images. Five indexes are used to evaluate the iris images. These indexes are eyelid occlusion, living, definition, eyelashes occlusion and cosmetic contact lenses respectively. In this way,...
A novel iris image segmentation method using watershed and region merging is put forward. Total variation flow model is used to divide the eye image into structure part and texture part. Light spots in pupil are removed by closing. Watershed and region merging are both applied in structure part. Structure part is divided into separate parts. The regions may contain iris are labeled. Then, merging...
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