• Journal of Multimedia Information System
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• 제5권4호
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• pp.221-228
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• 2018

Skin-color information is not sufficient for palmprint segmentation in complex scenes, including mobile environments. Traditional active shape model (ASM) combines gray information and shape information, but its performance is not good in complex scenes. An improved ASM method is developed for palmprint segmentation, in which Perux method normalizes the shape of the palm. Then the shape model of the palm is calculated with principal component analysis. Finally, the color likelihood degree is used to replace the gray information for target fitting. The improved ASM method reduces the complexity, while improves the accuracy and robustness.

• Journal of Multimedia Information System
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• 제5권3호
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• pp.179-188
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• 2018

In order to overcome the problems of contact palmprint recognition, a non-contact palmprint recognition system is developed on personal computer (PC) platform. Three methods, namely "double-line-single-point" (DLSP), "double-assistant-crosshair" (DAC) and "none-assistant-graphic" (NAG), are implemented for the palmprint localization to solve the severe technical challenges, including the complex background, variant illuminations, uncontrollable locations and gestures of hands. In NAG, hand segmentation and the cropping of region of interest are performed without any assistant graphics. The convex hull contour of hand helps detect the outside contour of little finger as well as the valley bottom between thumb and index finger. The three methods of palmprint localization have good operating efficiency and can meet the performance requirements of real-time system. Furthermore, an attendance system on PC platform is designed and developed based on non-contact palmprint recognition.