Statistical method for segmentation of fingerprint images for an image retrieval system
Charles Hawkins, David M. Holburn · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1993
An improved technique is described for segmentation of digitized grey scale image of fingerprints. Conventional approaches to the segmentation problem are apt to yield binarized images of acceptable visual clarity, but tend to emphasize noise, which may lead to inefficiency in data compression and storage. They may be computationally intensive, which has implications on time taken for the processing of current archives. The advantages of the technique described are high visual acceptability of the resulting binary images, and speed of execution using simple computing architectures. The method makes use of a matched spatial domain high pass filter, combined with a statistical operator that attenuates noise and effects due to paper grain. Examples are presented of the use of the technique with fingerprint images of widely varying quality, and it is shown that visually acceptable results are obtained even when the original images is heavily degraded. Results after compression are described showing merits of the statistical operator.