Hand Image Feature for Human Identification
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Abstract
Description
This paper presents an algorithm for efficient personal identification using robust hand
features. The feature is extracted from hand boundary points and print of hand palm. The centre of
gravity of the edge map of the hand image is determined to serve as a reference point. Thereafter
City block distances between the reference point and hand boundary points are found. These
distance feature vectors are compared using Euclidean distance measure for effective image
classification. The proposed algorithm will improve personal identification in access control and
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TK Electrical engineering. Electronics Nuclear engineering