Abstract
A method for fingerprint matching using invariant moment features is proposed. The fingerprint image is first preprocessed to enhance the original image by the Short Time Fourier Transform (STFT) analysis. Then, a set of seven invariant moment features is extracted to represent the fingerprint image from a Region of Interest (ROI) based on the reference point of the enhanced fingerprint image. The reference point is determined by the complex filters method. Finally, a Back Propagation Neural Network (BPNN) is trained with the features for matching. Experimental results show the proposed method has better performance with higher accuracy and faster speed comparing to the traditional Gabor feature-based fingerCode method. © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Yang, J. C., Shin, J. W., & Park, D. S. (2007). Fingerprint matching using invariant moment features. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4456 LNAI, pp. 1029–1038). Springer Verlag. https://doi.org/10.1007/978-3-540-74377-4_108
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