Butterfly Image Classification Using Color Quantization Method on HSV Color Space and Local Binary Pattern

Dhian Satria Yudha Kartika (Department of Informatic Engineering, Faculty of Information Technology, Institut Teknologi Sepuluh Nopember (ITS), Kampus ITS Sukolilo, Surabaya 60111, Indonesia)
Darlis Herumurti (Department of Informatic Engineering, Faculty of Information Technology, Institut Teknologi Sepuluh Nopember (ITS), Kampus ITS Sukolilo, Surabaya 60111, Indonesia)
Anny Yuniarti (Department of Informatic Engineering, Faculty of Information Technology, Institut Teknologi Sepuluh Nopember (ITS), Kampus ITS Sukolilo, Surabaya 60111, Indonesia)

IPTEK Journal of Proceedings Series
No 1 (2018): 3rd International Seminar on Science and Technology (ISST) 2017

A lot of methods are used to develop on image research. Image detection to relay back new information, widely used in various research field, such as health, agriculture or other field research. Various methods are used and developed to get better results. A combination of several methods is performed for testing as part of the research contribution. In this study will perform the combination results of the process color feature extraction with texture features. In color feature extraction using HSV color space method that gets 72 feature extraction and on texture feature extraction using local binary pattern that gets 256 feature extraction. The process of merging the two extracted results gets 328 new feature extractions. The result of combining color feature extraction and texture feature extraction is further classified. Results from image classification of butterflies get an accuracy score of 72%. The results obtained will be tested performance. The results obtained from performance testing get precision value, recall and f-measure respectively 76%, 72% and 74%