Research On Algorithm For Palmprint Localization And Recognition

Nowadays, information technology comes more nearer into our life. People attach more importance to technology security with the development of the technology society. Biometrics combines biology technology and information technology to exploit physical features in human body such as fingerprint and palmprint or behavioral features such as gait and signature to identify a person. This new technology has no disadvantages of the traditional methods such as: easy to lose or forget. This new technology can be applied to information security. Biometric is becoming one of the highest potential technologies in 21th century.Palmprint recognition exploits the large amount of information on our palm to identify different persons. Palmprint includes a great deal of information, and it is unique. Therefore, it is suitable for personal identification. So, palmprint has drawn great attentions from many research teams from allover the world. As a result, various palmprint identification methods have been proposed. This thesis concentrates on the research of the key technologies, according to the characteristic of palmprint. We first propose an efficient algorithm of region of interest extraction for palmprint images. And we also propose two efficient algorithms of palmprint feature extraction. To be more specific, the main achievements in this paper are as follows:1. To summarize the development of the state of the art of the biometrics technologies, analyze the characteristic of palmprint identification methods, and compare the virtues and drawbacks.2. To present a new method of extracting the region of interest of palmprint images: Different palms have different sizes, and because of the translational and rotational placements of hands, the collected palmprint images from the same palms are different from time to time. Therefore, it is essential to preprocess the palmprint images to obtain region of interest of palmprint images.3. To propose novel feature extraction methods for palmprint recognition: Palmprint can be used for personal identification because every one has different features in their hands. How to extract the features is one of the key problems to obtain highly accurate and reliable palmprint identification systems. We present two feature extraction methods, i.e., 2DPCA-based pamprint feature extraction and an enhanced operator of texture for palmprint recognition.