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| Detection Change on Fingernail Biometric using Machine Learning |
Rugaia. O. Ahmed , Amine Babiker A.Nabi, Adam M A.Bakheet Mashaer A. Hussein and Abdalsakhi.S.Mohammed
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Abstract:
This study focuses on detection change on fingernail biometric using Machine Learning, analysis of fingernail image for person that capture, monitored, and photographed for 90 days. It used an image processing system which includes image segmentation, color threshold, and shape analysis. The fingernail database used are classified using (Statistics and Machine Learning Toolbox(tm)) on the extracted features. The proposed detection accuracy training in the machine learning (0.9545 at first day, 0.7333 at eight days and 0.2267at 90 days). It was matched with the support our hypothesis which said that the fingernail is transient biometric trait that is change during three months.
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