Obtaining valid iris texture is the precondition of iris based personal verification and identification. With a special camera, illumination environment and users' cooperation play an important role in capturing high quality iris image. However, the captured iris images are usually corrupted by partial occlusion (by eyelids and eyelashes) and white spots (from specular refection). An efficient scheme of obtaining valid iris texture is described in this paper. The described scheme includes two parts: a new algorithm for locating iris texture and a novel algorithm for segmenting corrupted iris texture. In order to overcome the drawbacks of traditional iris texture location methods, which are sensitive to white spots and occlusion, a new location algorithm is proposed. The proposed location algorithm is able to locate iris texture rapidly by avoiding the tremendous computation demands imposed by Canny detector, Hough transformation and integrodifferential operator. In addition, a novel segmentation algorithm is proposed in the latter part of this paper to exclude the occlusion regions from the corrupted annular iris texture. Experiments show that the proposed scheme is efficient and robust for obtaining valid iris texture, even if partial occlusion and white spots appear. Moreover, the average time cost of our scheme is about 150ms on Pentium IV 2.8GHz PC, which satisfies the real-time requirement.
An improved live-wire algorithm is presented for interactive weak edge detection and extraction. In comparison with live-wire algorithm, the proposed one, with the same complexity as the original one, greatly improves its performance in edge detection of region of interest (ROI). Meanwhile, the modified algorithm overcomes the following drawbacks of the traditional one: (1) rather sensitive to noise, (2) inefficient to distinguish between the strong and the weak edges, (3) inapplicable to detect sharp edges. The experimental results illustrate that the proposed algorithm is really of good performance over the traditional one in three aspects.