Name
Abstract | ||
|---|---|---|
Image segmentation is one of the most important tasks in the image processing, and many algorithms for the segmentation have been proposed. In the segmentation based on the mean-shift, k-means and so on, the image is once over-segmented, and then the small regions are merged. In this paper, we propose a region merging algorithm for hardware systems, in which the data are not managed strictly, and the redundant computation caused by this loose management is hidden by the pipelined and parallel processing. We have implemented the algorithm on Xilinx XC4VLX160, and its performance is about 80 fps for 768 × 512 pixel images. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/FPL.2012.6339166 | FPL |
Keywords | Field | DocType |
parallel processing,image processing,image segmentation,pixel images,k-means algorithm,hardware systems,fpga,field programmable gate arrays,region merging approach,mean-shift,xilinx xc4vlx160,pipelined processing | Computer vision,Scale-space segmentation,Feature detection (computer vision),Computer science,Binary image,Image processing,Segmentation-based object categorization,Image segmentation,Artificial intelligence,Digital image processing,Minimum spanning tree-based segmentation | Conference |
ISBN | Citations | PageRank |
978-1-4673-2255-3 | 1 | 0.42 |
References | Authors | |
5 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dang Ba Khac Trieu | 1 | 21 | 2.90 |
| Tsutomu Maruyama | 2 | 559 | 72.14 |