IDENTIFIKASI CITRA BAHAN KULIT HEWAN MENGGUNAKAN METODE LOCAL BINARY PATTERN DAN GRAY LEVEL RUN LENGTH MATRIX DENGAN METODE KLASIFIKASI NEURAL NETWORK - Maulana Hafizd, (2020)
Leather is one of the oldest and the most useful discovery for humans. Leather is processed into various kinds of products that are useful to fulfill human needs such as shoes, wallets, bags, and so on. The motifs and quality of leather vary according to the type of animal used. This causes the selling price of leather to vary depending on the quality and type of animal used. A common difficulty is that animal skin products are similar in appearance. This can cause limitations in the ability of consumers to know the types of animals used. This limitation affects consumers in knowing the selling price and quality of the leather. The development of science in the digital image processing allows humans to overcome these problems. Different motifs on leather can be identified by texture analysis. Local Binary Pattern (LBP) and Gray Level Run Length Matrix (GLRLM) are used as a method for extracting texture features, and Neural Network (NN) is used as a classification method. In this research, the images of leathers are divided into five categories, that are cow, pig, sheep, goat, and kangaroo. This research is expected to produce a system that is able to identify the image of leather according to the category of animal species used.