IDENTIFIKASI SIDIK JARI MENGGUNAKAN JARINGAN SYARAF PROPAGASI BALIK DAN LEARNING VECTOR QUANTIZATION BERBASIS MINUTIAE FITUR BIFURCATION
Daftar Isi:
- Fingerprint identification is useful for determining ownership of fingerprints. This determination is based on minutiae. There are several minutiae features and in this study the features used are the bifurcation-feature minutiae. To identify fingerprints based on the bifurcation-feature minutiae, back propagation and learning vector quantization methods are used. The results of this study found that the average back propagation accuracy reached 87.5%, the accuracy of learning vector quantization reached 50%, the average back propagation process time was 0.37378 seconds, and the average learning vector quantization process time was 0.36941 seconds .