K-Nearest Neighbor (k-NN) Classification for Recognition of the Batik Lampung Motifs

Abstract

Batik is a famous name of a traditional fabric from Java. It has been admitted as one if the traditional cultural heritage of Indonesia by UNESCO since October 2nd, 2009. Over the time, Batik is copied and modified by many regions in Indonesia resulting some new unique motifs. Batik Lampung is an sample of them. This paper deals with the k-Nearest Neighbor classification of the motifs (pattern) of the Batik Lampung. The known motifs of Batik Lampung consist of Jung Agung, Siger Kembang Cengkih, Siger Ratu Agung, and Sembagi. The original image samples are stored in RGB. They are firstly resized into 50 x 50 pixels and then converted to grayscale image. To recognize them, the Gray Level Co-Occurence Matrix (GLCM) feature is extracted and k-Nearest Neighbor (k-NN) with values of k = 3, 5, 7, 9, 11 and orientation angle of 0 45, 90, 135 is applied to classify the motifs. The best accuracy is achieved at the rate 97,96% for k = 7 and angle135.