Palmprint recognition using wavelet
Palmprint is a relatively new biometric feature, and is regarded as one of the most unique, reliable, and stable personal characteristics. A palm is an inner surface of the hand between the wrist and the fingers . Palm has several features to be extracted like principal lines, wrinkles, ridges, singular points, texture and minutiae. Principal lines are the darker line present on the palm. There are 3 principal lines on the palm namely, heart line, head line and life line. Wrinkles are the thinner lines concentrated all over the palm. Normally people do not feel uneasy to have their palmprint images taken for testing. On palms lines and textures are more clearly observable features. Lines are more appealing than texture for human vision. When human beings compare two palmprint images, they instinctively compare line features. But extracting principle lines and creases is not an easy task because it is sometimes difficult to extract the line structures that can discriminate every individual well.
KeywordsFeature Vector Recognition Rate Wavelet Transform Principal Line Palmprint Image
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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