Automated Fingerprint Identification System (AFIS) has widespread usage in practice. Fingerprint image enhancement and minutiae matching is two of the key problems in AFIS. In this dessertation, we proposed a fingerprint image enhancement algorithm based on orientation field. In addition, we proposed a minutia matching algorithm which modified Jain et al.'s algorithm. In our algorithm, a simpler alignment method is used. We introduced ridge information into the minutiae matching process in a simple but effective way. One of the advantages of doing so is we solved the problem of reference point pair selection with low computational cost. In addition, we used changeable sized bounding box to make our algorithm more robust to nonlinear deformation between fingerprint images. Experiments done on the FVC2000 databases with the FVC2000 performance evaluation method show that our improved algorithm is better than the original one. Image segmentation is one of the classical difficult problems. Many researchers had worked on this problem ever since 1970s. But no method that had good result for general images had been proposed and no impersonal criterion for deciding whether the segmentation is success had been generally accepted up to now. In this dessertation, we give a rather complete survey to the image segmentation methods, especially those new ideas, new methods and new improvement to the classical methods appeared in the literature of the last few years. The maximum entropy approach is one of the most important threshold selection methods in image processing. Many authors avoid the problem of computationally prohibitive when the maximum entropy criterion is applied to multi-level threshold selection. This dessertation proposed to deal with this problem using ICM(iterated conditional modes) algorithm. Experiments done to compare our ICM algorithm with the simulated annealing algorithm proposed by Cheng et al. fully disposed the effectiveness of ICM algorithm. The maximum entropy approach is one of the most important threshold selection method, H.D.Cheng et al. introduced fuzziness into maximum entropy approach and proposed the fuzzy maximum entropy criterion. In this dessertation, we do some modifications to their method, give our own formulation and propose to solve the problem of computationally prohibitive when the fuzzy entropy criterion is applied to multi-level threshold selection using ICM algorithm. Experiments comparing our ICM algorithm with the simulated annealing algorithm proposed by them fully disposed the effectiveness of our method. In this dessertation, we propose an algorithm for the semiautomatic segmentation of medical image series based on the combination of the live wire algorithm and the active contour model. We modify the traditional live wire algorithm by combining it with the region growing method and obtain accurate segmentation of one or more slices in a medical slice seri
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