Machine vision
Pattern recognition and image analysis
Pattern recognition and image analysis
High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Processing, Analysis, and Machine Vision
Image Processing, Analysis, and Machine Vision
A study on fast iris image acquisition method
CAIP'05 Proceedings of the 11th international conference on Computer Analysis of Images and Patterns
A real-time iris image acquisition algorithm based on specular reflection and eye model
ACIVS'05 Proceedings of the 7th international conference on Advanced Concepts for Intelligent Vision Systems
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In this paper, we propose a fast circular edge detector for the iris region segmentation by detecting the inner and outer boundaries of the iris. In previous work, the circular edge detector which John G. Daugman proposed, searches the radius and the center of the iris to detect its outer boundary over an eye image. To do so, he used Gaussian filter to smooth texture patterns of the iris which cause its outer boundary to be detected incorrectly. Gaussian filtering requires much computation, especially when the filter size increases, so it takes much time to segment the iris region. In our algorithm, we could avoid procedure for Gaussian filtering by searching the radius and the center position of the iris from a position being independent of its texture patterns. In experimental results, the proposed algorithm is compared with the previous ones, the circular edge detector with Gaussian filter and the Sobel edge detector for the eye images having different pupil and iris center positions.