Palmprint feature extraction based on wavelet transform
Tianhuai Ding · Journal of Tsinghua University(Science and Technology) · 2003
Ridge orientations and ridge spatial frequencies in various regions of the palm represent the intrinsic characteristics of a palmprint image. Palmprint features were accurately extracted using an algorithm based on wavelet transforms of the original gray scale image. The features were extracted directly from the gray scale palmprint image without preprocessing (i.e. image enhancement, filtering, region segmentation, binarization, ridge thinning, etc.), and hence the proposed algorithm requires less computational effort than conventional algorithms based on minutiae features. The algorithm can achieve high recognition rates when a test is on a small palmprint database using the Knearest neighbor (KNN) classifier.