Clustering based image segmentation in this study using Fuzzy C means algorithm with Xie Beni Index as an objective function. Preprocessing applied in this model using Statistical Region merging. Spatial function applied in Fuzzy C means method to reduce noise in clustering. The system evaluation is done by measuring cluster validity value (Xie Beni Index), execution time, and number of iteration. Experimental results on three test images illustrates the proposed method able to perform image segmentation well.

Balinesse lontar digitalization generates image file which acquired through a scanner or camera. Lontar image has noise because the results of the acquisition of the original lontar contained brown color that exist on the leaves. Therefore this paper focuses on improving the quality of the image to remove noise contained in the image by thresholding process. The method used in this paper is a Local Adaptive Thresholding. The test results in this paper generates the best image with the window (W)=70 and the threshold value (C)=0.05 which proved to remove noise at most of the few testing that has been done in this paper