Feature Extraction Algorithms Research Of Palmprint Recognition That Based On Gabor

People attach more importance to technology security with the development of the technology society. Traditional security and authentication can not guarantee the safety of authentication. However, biometrics based on personal biologic feature can solve the authentication problems efficiently and safely, which is concerned widely. Biometrics combines biology technology and information technology to exploit physical features in human body such as fingerprint, iris, face and palmprint or behavioral features such as gait and signature to identify a person. Now it is considered as the highest-ranking security key system in the highly interconnected information society. This new technology can be applied to homeland security, social welfare, financial and e-commerce, and it is becoming the highest potential technology in this era.The palmprint recognition is a new biometrics technology, which use palm texture as biologic characters to recognize identity. As palmprint is typical of ease acquisition, and its major feature is apparent, stability and divisibility, palmprint automatic identification is a very potential identification technology.The thesis mainly investigates in palmprint recognition feature extraction. In detail, this dissertation concentrates on the research of the following key:1. Discuss the meaning, history, developing and the state of biometric and palmprint recognition, some common biometric identification technologies are briefly introduced and give an outline of palmprint recognition system and its rule evaluation.2. Through the structural characteristics and advantages of palmprint, the basic identification processing of palmprint, the acquisition technologies of palmprint images, and the development status quo of palmprint's research, we detailed described about palmprint identification technology.3. Summarize some feature extraction methods of the palmprint recognition and some of methods are talked in detail.4. An improved palmprint recognition method using Gabor wavelets and 2-Dimentional Principal Analysis (2DPCA) are proposed.2DPCA in this method overcomes the curse of dimension of traditional PCA after Gabor wavelets transform. And an improved palmprint recognition method based on traditional PCA and FLD is proposed. In this method, PCA features are used again in recognition stage. Simulation results show that the proposed method can get more recognition rate with lower dimensions.5. A palmprint recognition method using Gabor wavelets and 2D-2DPCA are proposed. The new method 2D-2DPCA use 2DPCA twice:one was in horizontal direction and the other in vertical direction. The pertinency of rows and columns in palmprint image is avoided. Simulation results show that the method is more effective and simple in recognition.