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jly_jly捐助贵宾 (小有名气)
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[求助]
请高手帮翻译一个项目摘要，谢谢！
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快速准确地检测圆是许多工业领域中的一个难题，如自动化检验和装配、机器人技术、视频检测、粒子跟踪及动作捕获等，在模式识别和计算机视觉领域有着广泛的应用前景。项目研究快速、精确、内存需求低、适用性强的圆检测方法，主要从以下三个方面展开研究：(1)Hough变换(Hough Transformation)是检测圆的基本工具，项目将针对随机Hough变换存在的计算量大和占用内存大等缺点进行深入分析，研究能快速计算、大量降低内存需求同时又能保证精确度的圆检测方法，以满足实际应用的需要；(2)针对随机圆检测算法(Randomized Circle Detection)对于多圆复杂图像需耗费大量的计算时间，从采样方法和证据积累等方面进行优化以提高检测速度；(3)用C++语言编程实现项目中提出的圆检测思想，结合图像处理知识，构建一个能对图像中的圆进行检测的应用软件。 /////////////////////////////////////////// 另，第一句可提供如下一个类似的翻译参考。 The fast and accurate detection of circles is a challenge in many industrial fields, including video inspection, particle tracking, robotics, neurosurgery, archeology, biology, and motion capture. |
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铁杆木虫 (职业作家)
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【答案】应助回帖
★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ...
sltmac(金币+2): 2012-03-07 18:10:00
jly_jly(金币+50, 翻译EPI+1): ★★★★★最佳答案 谢谢，辛苦了，呵呵 2012-03-09 01:18:09
sltmac(金币+2): 2012-03-07 18:10:00
jly_jly(金币+50, 翻译EPI+1): ★★★★★最佳答案 谢谢，辛苦了，呵呵 2012-03-09 01:18:09
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供参考： 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. |
2楼2012-03-07 17:43:34
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