Batik, as a cultural beritage from Indonesia, has a lot of motifs based on certain patterns. This paper discausses feture extraction methods for the recognition of batik motifs in digital images. In this study, the use of several feature extraction methods have been compared in terms of their performance with several scenarios for testing level accuracy. The methods include Gray level Co-occurrence matrices (GLCM), Canny edge detection , and Gabor filters. The experimental result show that the use of GLCM features has performed the best with a classification accuracy reaching 80 %.