In this paper, we propose a new online palmprint verification method, providing a more convenient way to users when
having palmprint images captured. Unlike other palmprint verification methods, which use positioning pods to fix the
location of a palm, we suggest capturing a palmprint without using any devices to locate the palm. Therefore it makes the
users more comfortable but requires better positioning algorithm to locate the palmprint automatically. Here we propose
an inscribe circle based palmprint positioning and interesting area extraction algorithm to deal with the palmprint
position variation introduced in capturing. We also suggest using the histogram stretching to eliminate the impact of
environment light variation. We suggest using the Niblack method to extract the principle lines on a palm and proposed a
bi-directional matching method for similarity measurement. The experimental results demonstrate the effectiveness of
our method.
Usually we accept it as a fact that one person's left and right hands are symmetric in some degree. But we don't know
exactly how similar they are. In this paper, we designed an experiment to illustrate it in numbers that two palms from one
person are more similar than two palms from two persons. This similarity may enable us to register on a palmprint
verification system with one hand and go through the system with the other hand. We also designed another interesting
experiment to tell that when doing personal verification by looking at the palmprint pictures, human beings cannot be
100 percent correct as we assumed before. Under certain circumstance, the machine can do a better job than a person.
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