A Palmprint Recognition Approach Based on Image Segmentation of Region of Interest

Abstract

To carry out an effective recognition for palmprint, this paper presents an algorithm of image segmentation of region of interest (ROI), extracts the ROI of a palmprint image and studies the composing features of palmprint. This paper constructs a coordinate by making use of characteristic points in the palm geometric contour, improves the algorithm of ROI extraction and provides a positioning method of ROI. Moreover, this paper uses the wavelet transform to divide up ROI, extracts the energy feature of wavelet, gives an approach of matching and recognition to improve the correctness and efficiency of existing main recognition approaches, and compares it with existing main approaches of palmprint recognition by experiments. The experiment results show that the approach in this paper has the better recognition effect, the faster matching speed, and the higher recognition rate which is improved averagely by 2.69% than those of the main recognition approaches.

Magnetostatic Active Contour Model with Classification Method of Sparse Representation

“…Weizmann database is used to support this study which is shown in [39]. ese prior studies are cited at relevant places within the text as [1,2].…”

“…Image segmentation aims to separate the "target" area and the "background" area of the input image and to extract the interesting part for in-depth understanding and analysis [1,2]. Segmented images are the advanced expression of the original pixels to semantic objects.…”