Summary: For personal identification, fingerprint identification has been much more widely used than other automatic biometric identification methods. For reliable feature extraction we analyze the direction of ridges, and the structural characteristics, such as the ridge line width and interval, are automatically estimated based on the ridge line following algorithm. To eliminate false features outside the region of interest, we generate adaptive matching boundaries. The concept of fuzzy sets is applied to the extracted features and the quantitative feature values are defined. In the feature matching stage, we introduce a weighted matching score using quantitative feature values to guarantee reliable matching results. Furthermore, a two-step estimation of transformation parameters is employed to reduce the computational complexity. The experimental results show that our system can achieve a fast personal identification with a good performance.
For the entire collection see [Zbl 0996.00020].