Performance Evaluation of Fingerprint Identification Based on DCT and DWT Using Multiple Matching Techniques
The fingerprint is a physiological trait used to identify a person. In this paper, Performance Evaluation of Fingerprint Identification based on DCT and DWT using Multiple Matching Techniques (FDDMM) is proposed. The fingerprint is segmented into four cells of each size 150240. The DCT is applied on each cell. The Harr Wavelet is applied on DCT coefficient of each cell. The directional information features and centre area features are computed on LL sub band. The final Feature Vector is obtained by concatenating Directional Information and Centre Area Features. The matching techniques viz., ED, SVM, and RF are used to compare test image feature with database image features.