Monkey Types Classification Based On Image Using The Gray Level Co-occurrence Matrix (glcm) Method And Support Vector Machine (Svm)

Muhammad Rizky Anugrah Sakti, Febryanti Sthevanie, Kurniawan Nur Ramadhani

Abstract

Abstract Monkeys have many types, they are still categorized into 2 parts, namely from the old world and new world. There are only 260 recorded types of monkeys that have existed until now, in the next few years there could be new types of monkeys that will be discovered by experts. Monkeys are intelligent creatures and monkeys are unique animals because their intelligence is almost equal to toddlers. In the future animals especially monkeys and humans continue to evolve, so there may be monkeys with new species and with a new type of intelligence. The development of modern technology, especially in computer vision is very necessary because computers have a hard time distinguishing an animal especially if the differences only in color. There have been many studies on animal recognition or classification using image processing techniques. However, some of these studies are still in a very broad scope and are not focused on one problem. For author cases, there is still few experiments classified type of monkey. Therefore, the author proposed a system using grey-level co-occurrence matrix (GLCM) and Color Histogram mean extraction method, while the classification is using the Support Vector Machine (SVM) method. The result from the experiment is obtained from f1-score, for validation accuracy is 88,66% and test accuracy are 90%.
Keywords: Monkey classification, SVM, GLCM, Color Histogram, machine learning.

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