K-means clustering is a very popular clustering technique, which is used in numerous applications. However, clustering is a time consuming task, particularly for large dataset, and large number of clusters. In this paper, we show that real-time k-means clustering can be realized for large size color images (24-bit full color RGB) and large number of clusters (up to 256) using an off-the-shelf FPGA (Field Programmable Gate Arrays) board. In our current implementation with one FPGA, the performance for 512 ? 512 and 640 ? 480 pixel images is more than 30 fps, and 20 - 30 fps for 756 ? 512 pixel images in average when dividing to 256 clusters.