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Subset Image Extraction and Comparison to Identify Different Fingerprints

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This study uses the moment invariant technique to locate the orientation of an object. A bifurcation-extraction algorithm is used to extract the bifurcated images of fingerprints. All the subset images of these bifurcations are explored, extracted and subsequently compared to other subset images extracted from other bifurcations to discover the best match for identifying the fingerprint images. An image database is established and used to classify the bifurcations. The following techniques are used to recognize the fingerprint images: bifurcation-point automatic detection, image automatic orientation detection, subset image extraction and image database establishment, as well as image rotation and subtraction, and sub-pattern image convolution. The algorithm developed in this study can precisely classify the bifurcated images.
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Document Type: Research Article

Publication date: 01 June 2008

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  • The growing interest and activity in the field of sensor technologies requires a forum for rapid dissemination of important results: Sensor Letters is that forum. Sensor Letters offers scientists, engineers and medical experts timely, peer-reviewed research on sensor science and technology of the highest quality. Sensor Letters publish original rapid communications, full papers and timely state-of-the-art reviews encompassing the fundamental and applied research on sensor science and technology in all fields of science, engineering, and medicine. Highest priority will be given to short communications reporting important new scientific and technological findings.
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