Principle Line Extraction and Restoration Based on Wavelet Theory
Qimei Liao · 2006
As a vital branch in the study of biometrics-based technology,identification and verification by palm print has been a striking evidence for prior disease diagnosis and personal recognition,given its remarkable advantages like simplicity and stablility,etc.Especially,the extraction process of principle-line feature plays a key role.This paper presents a new approach to extract this novel characteristic.Unlike other traditional methods,its step is inherently simple and convenient using regular scanner.After the pre-process and alignment,we extract four spatial directional template and reach high convergence by adopting Symlet wavelets transformation method,and a series of morphological operations derived from ASF are utilized.Finally we use regression analysis and image fusion to eliminate divergence and disconnectedness in our result region,and successfully extract principle-line from numerous palm-lines.The experimental results with a large collection of different images showed its advantages compared with former work,and also illustrated its strong robustness,and provide effective and accurate statistics to clinical diagnosis,classification and encoding work at a later stage.