Abstract
Image retrieval is an image search method by performing a comparison between the query image and the image contained in the database based on the existing information. This study proposes to save the characteristic of Indonesian batik, so the system can help in the prevention of claims from other countries. This study discusses the content-based image retrieval using Multi Texton Histogram and Invariant Moment. MTH is known as a method of describing the characteristics of the surface texture, and IM is a method that produces characteristic geometry of an object and the introduction of geometry that are independent of translation, rotation, and scaling. This study used 10,000 each Batik and Corel images as datasets. The system will take random sample of 7,000 images as training data and the rest is used as the testing data. As the result, Batik Dataset produces precision of 99.75% and a recall of 14:25%. While Corel Dataset produces precision of 36.63% and a recall of 5:23%. The system generates a better performance in the Batik dataset because batik texture is monotonous. While, the Corel dataset has more diversified of the shape and texture.
 
 Keywords: Batik, Image Retrieval, multi texton histogram, invariant moment