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sltmac(½ð±Ò+2): 2012-03-07 18:10:00
jly_jly(½ð±Ò+50, ·ÒëEPI+1): ¡ï¡ï¡ï¡ï¡ï×î¼Ñ´ð°¸ лл£¬ÐÁ¿àÁË£¬ºÇºÇ 2012-03-09 01:18:09
sltmac(½ð±Ò+2): 2012-03-07 18:10:00
jly_jly(½ð±Ò+50, ·ÒëEPI+1): ¡ï¡ï¡ï¡ï¡ï×î¼Ñ´ð°¸ лл£¬ÐÁ¿àÁË£¬ºÇºÇ 2012-03-09 01:18:09
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¹©²Î¿¼£º Quick and accurate detection of circles is a challenge in many industrial fields, such as automated inspection and assembly, robotics, video detection, particle tracking, motion capture, etc., and there exist promising prospects its application in the fields of pattern recognition and computer vision. The project carried out research on quick, accurate, low memory, and universally applicable circle detection methods with a special emphasis on the following 3 aspects: (1) Targeting at Hough Transformation, a basic tool for circle detection, the research was focused on the in-depth analysis of some disadvantages of the randomized Hough Transformation including large calculation and memory required. Based on the analysis, research was conducted on high speed based accurate circle detection methods requiring dramatically reduced memory, so as to meet the needs of practical application. (2) Regarding the great amount of time for calculation take by the Randomized Circle Detection algorithm in processing complex multi-circle images, optimization was applied to the sampling methods, accumulation of evidence, etc. with a view to improving the detection speed. (3) The C++ programming language was employed to achieve the circle detection ideas proposed by the project, and in combination with image processing knowledge, application software was built for detecting the circles in images. |

2Â¥2012-03-07 17:43:34













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