Biography of

His current research interests include computer vision, pattern recognition and special architectures for vision and image processing. He is a student member of IEEE. both in computer science. He is currently a Ph.D. student at Michigan State University. His current research interests include pattern recognition, machine vision and their applications in robotics. India. He has also been a consultant to several industrial, government and international organizations. His current research interests are computer vision, image processing, neural networks and pattern recognition. Dr. Jain has made signiicant contributions and published a large number of papers on the following topics: statistical pattern recognition, exploratory pattern analysis, neural networks, Markov random elds, texture analysis, interpretation of range images, and 3D object recognition. Several of his papers have been reprinted in edited volumes on image processing and pattern recognition. He received the best paper awards in 1987 and 1991, and received certiicates for outstanding con-Summary In this paper, we have proposed a reliable method for feature extraction from ngerprint images. The ow direction of the ridges is computed viewing the ngerprint image as a textured image. The ridge ow direction plays an important role in adapting lters for rest of the stages in our algorithm. A waveform projection-based algorithm is described for extracting the ridges. Using morphological lters, the thinned skeleton of the ridges are smoothed. The structural features are extracted from the skeleton image. A postprocessing stage deletes spurious minutiae. The performance of the proposed algorithm is evaluated by computing a \goodness index" (GI). The extracted features have been shown to be reliable and accurate on the basis of the signiicance of the observed GI values of a set of ngerprints in comparison with the GI values obtained under a baseline distribution. Abstract A reliable method for extracting structural features from ngerprint images is presented. Viewing ngerprint images as a textured image, an orientation ow eld is computed. Rest of the stages in the algorithm use the ow eld to design adaptive lters for the input image. To accurately locate ridges, a waveform projection-based ridge segmentation algorithm is used. The ridge skeleton image is obtained and smoothed using morphological operators to detect the features. A large number of spurious features from the detected set of minutiae is deleted by a postprocessing stage. The performance of the proposed algorithm has been evaluated by computing a \goodness index" (GI) which compares the results of automatic extraction …