PENGENALAN CIRI GARIS TELAPAK TANGAN MENGGUNAKAN EKSTRAKSI FITUR (GLCM) DAN METODE K-NN - Intan Purnamasari; T. Sutojo (Universitas Raharja, 2017)
The necessity of trustworthy self-introduction is increasing for safey system.Biometric is a development of person basic identification using human natural characteristic, in this case is palm of hand.Palmprint biometric is choosen for it has a unique characterisctic including tangled lines (wrinkles features) and are stable. The main thing of this question is “what is my identity similar with the thing that I mention or guess?”.In this analysis, the writer chooses KNN method and extract of GLCM features to solve this research.The sequences of the reseacrh begin with a sample of palmprint, then it continues by changing the image of RGB to grayscale. The output of the prepocessing is extracted by using GLCM features.The next step is classifying between trained image and tested image using K-NN method. The result of the classification is measured based on level of its accuration and comparing the accuration result by changing directed corner to GLCM and total of K in K-NN.In the research, the sample used by amount of 103 images which consist of 78 palmprint image for trained image and 26 tested image on each respondents represented by 4 samples of palmprint. Then, the output of total accuration is amount 92,3%