Name
Abstract | ||
|---|---|---|
This paper develops a hardware-efficient color segmentation algorithm that is especially suitable to implement on hardware for face detection. Since the modulized design is adopted in the proposed algorithm without floating-point operation, the computational cost is directly reduced for hardware design. The proposed algorithm consists of a color space modeling module and a feature enhancement module. The significant skin/lip color features distribution can be accurately detected by using our proposed algorithm to facilitate the face detection. The proposed algorithm was implemented on a field-programmable gate array (FPGA) system for verifying its efficiency. Compared with other state-of-the-art algorithms, the proposed algorithm can significantly decrease the computational cost of the hardware implementation by using color segmentation instead of the overall analysis of the color distribution. Experimental results have verified that our proposed FPGA system occupies only 3,202 logic cells, or about five times less than the current comparable FPGA system with better detection rate. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/APCCAS.2010.5774971 | APCCAS |
Keywords | Field | DocType |
face detection,face recognition,field-programmable gate array (fpga),skin-lip color features,image segmentation,color segmentation,modulized design,color space modeling module,fpga system,feature enhancement module,object detection,floating-point operation,field programmable gate arrays,image enhancement,field-programmable gate array system,image colour analysis,hardware-efficient color segmentation algorithm,skin,field programmable gate array,floating point,algorithm design and analysis,face,feature extraction,hardware,color space | Color space,Computer science,Electronic engineering,Image segmentation,Artificial intelligence,Face detection,Computer hardware,Object detection,Computer vision,Algorithm design,Field-programmable gate array,Algorithm,Feature extraction,Gate array | Conference |
ISBN | Citations | PageRank |
978-1-4244-7454-7 | 2 | 0.39 |
References | Authors | |
5 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kai-Ti Hu | 1 | 12 | 0.89 |
| Yu-Ting Pai | 2 | 73 | 7.08 |
| Shanq-Jang Ruan | 3 | 375 | 55.44 |
| Edwin Naroska | 4 | 81 | 13.39 |