18th International Conference on Pattern Recognition (ICPR'06) Volume 2 Real-time K-Means Clustering for Color Images on Reconfigurable Hardware Hong Kong August 20-August 24 ISBN: 0-7695-2521-0
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2006.961
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.
Citation:
Tsutomu Maruyama, "Real-time K-Means Clustering for Color Images on Reconfigurable Hardware," icpr, vol. 2, pp.816-819, 18th International Conference on Pattern Recognition (ICPR'06) Volume 2, 2006 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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