Abstract
In this research, a new technique is used to extract the thumb, index, middle, ring, and small fingers and to perform a person’s identification. To allow the finger geometry to be more salient when performing the finger image comparison, the fingers are scaled to various sizes. For reducing the number of finger-image-files in the system, a person’s entire finger-images are placed in one file. The hand is fixed each time when a picture is taken and one can assume that each time when the hand image is taken, the acquired finger images are the same as the previously acquired ones. Since the pictures are the same, after the fingers are extracted from the hand image, one can use the acquired fingers to identify different people. In this research, the developed algorithm of the auto-registration technique can find the precise location of the finger image – including the centroid of the finger image and the orientation of the finger image. The finding of the position and the orientation of the finger image are conducted automatically and without any further human effort. After finding the positions of the finger images, image rotating, image shifting, and image interpolating techniques are used to align different finger images to the same position and the same orientation for comparison. The extracted finger image contains many useful geometrical features. One can use these features to do finger image identification. Since the entire finger images are aligned to the same position and the same orientation, the image phase-matching technique is used to examine the difference between two finger images. The image phase-matching technique involves complex number manipulation and also finds the most salient feature of the resultant images.
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