FINGERPRINT IDENTIFICATION TECHNIQUE BASED ON WAVELET-BANDS SELECTION FEATURES (WBSF)
Mustafa Dhiaa Al-Hassani, Abdulkareem Abdulrahman Kadhim, Venus W. Samawi · 2013
The paper is concerned with the use of fingerprint (FP)features for protection against unauthorized access. Wavelet features for both closed and open-set FP recognition are studied here to verify persons' identity. Fingerprints of 49 persons (32-authorized and 17-unauthorized) were taken as testing data. Each authorized person is asked to give 10-instances of his right forefinger print. In the closed-set FP recognition, the obtained recognition rates are below 90% due to the imperfections in the FP images that negatively affect the recognition rate. Preprocessing operations such as: noise-removal, segmentation, normalization and binarization are considered to improve the resulting recognition rates. A method that relies on a new selection process for wavelet decomposition bands is proposed, which enhance the recognition rates further to get about 100% in some favorable conditions. The results have shown that the wavelet descriptors using the proposed Wavelet-Bands Selection Features (WBSF) are efficient representation that can provide reliable recognition for large input variability. The open-set FP verification mode is also presented for 290 trials from 29 persons, where the obtained verification rates are greater than 97% for both Euclidean and city-block distance measures.