A Real-Time Image Segmentation on a Massively Parallel Architecture |
| |
| Affiliation: | 1. Fiontar, Dublin City University, Ireland;2. Universidad Politécnica de Cartagena, Spain;3. School of Business, Trinity College Dublin, Ireland;1. Department of Finance and Investment, College of Economics and Administrative Sciences, Al Imam Mohammad Ibn Saud Islamic University (IMSIU), PO Box 5701, Riyadh, Saudi Arabia;2. Higher Institute of Business Administration of Sfax (ISAAS), University of Sfax, Tunisia;3. Lebow College of Business, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104, United States;4. IPAG LAB, IPAG Business School, Paris, France;5. Saudi Electronic University, College of Administration and Finance, Saudi Arabia;1. Cardiff University, UK;2. CEPR, UK |
| |
| Abstract: | The method described in this paper enables the two end points of a straight line to be obtained by a Modified Double Hough Transform (MDHT). It consists respectively of line detection, followed by segment extraction. The significance of this work is that the hardware implementation is based on the Content Addressable Memory (CAM) concept. Hence, during the first HT, voting is achieved for the every scan line of image, not every edge pixel. Therefore, all the steps which form the first HT: voting, thresholding and local maximum are achieved in a low constant time. The two end points of the line are extracted through the second HT. Here, a local neighbor parallel search is also achieved at the end of each scan line of the image not at every edge pixel. Therefore, the execution time is low since the neighboring range does not exceed a few lines. Experimental results are given to show the accuracy of our approach for use in high performance pattern recognition systems. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
