<![CDATA[ABSTRACT:Image segmentation is the process of placing a label for each pixel in an image therefore pixels with the same label share certain visual characteristics. One of the algorithms that can be applied in accelerating the segmentation process is K-Means Clustering. K-means is a non-hierarchical clustering method that tries to partition existing data into one or more clusters. This method partitions data into clusters so that data with the same characteristics are grouped into the same cluster and data with different characteristics are grouped into other clusters. The implementation of the system uses the Visual Basic 2010 programming language and the method used in this research is the waterfall method. The results of the analysis carried out show that the similarity of the identified images based on the proximity of the color values and the accuracy produced is quite good, especially for objects that have special colors or colors that have become characteristics of the object. Keywords: Digital Image, Segmentation, Clustering, K-Means]]>
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