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

Abstract

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 2 nd , 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 0 45 0 , 90 0 , 135 0 is applied to classify the motifs. The best accuracy is achieved at the rate 97,96% for k = 7 and angle135 0 .