： This paper proposes a new sequential similarity detection algorithm （SSDA）, which can overcome matching error caused by grayscale distortion; meanwhile, time consumption is much less than that of regular algorith...： This paper proposes a new sequential similarity detection algorithm （SSDA）, which can overcome matching error caused by grayscale distortion; meanwhile, time consumption is much less than that of regular algorithms based on image feature. The algorithm adopts Sobel operator to deal with subgraph and template image, and regards the region which has maximum relevance as final result. In order to solve time-consuming problem existing in original algorithm, a coarse-to-fine matching method is put forward. Besides, the location correlation keeps updating and remains the minimum value in the whole scanning process, which can significantly decrease time consumption. Experiments show that the algorithm proposed in this article can not only overcome gray distortion, but also ensure accuracy. Time consumption is at least one time orders of magnitude shorter than that of primal algorithm.展开更多
针对移动机器人数字路标的识别提出一种增强的序贯相似性检测算法(SSDA,sequence similar detection arithmetic),算法中的阈值采用单调递减的阈值序列,阈值逐渐逼近最佳阈值,从而使非匹配区域经过尽量少的计算超过阈值而被丢弃,有效改...针对移动机器人数字路标的识别提出一种增强的序贯相似性检测算法(SSDA,sequence similar detection arithmetic),算法中的阈值采用单调递减的阈值序列,阈值逐渐逼近最佳阈值,从而使非匹配区域经过尽量少的计算超过阈值而被丢弃,有效改善识别的实时性。通过实验表明该算法能够快速准确地完成数字路标识别。展开更多
基金the National Natural Science Foundation of China(No.61165008)
文摘： This paper proposes a new sequential similarity detection algorithm （SSDA）, which can overcome matching error caused by grayscale distortion; meanwhile, time consumption is much less than that of regular algorithms based on image feature. The algorithm adopts Sobel operator to deal with subgraph and template image, and regards the region which has maximum relevance as final result. In order to solve time-consuming problem existing in original algorithm, a coarse-to-fine matching method is put forward. Besides, the location correlation keeps updating and remains the minimum value in the whole scanning process, which can significantly decrease time consumption. Experiments show that the algorithm proposed in this article can not only overcome gray distortion, but also ensure accuracy. Time consumption is at least one time orders of magnitude shorter than that of primal algorithm.
文摘针对移动机器人数字路标的识别提出一种增强的序贯相似性检测算法(SSDA,sequence similar detection arithmetic),算法中的阈值采用单调递减的阈值序列,阈值逐渐逼近最佳阈值,从而使非匹配区域经过尽量少的计算超过阈值而被丢弃,有效改善识别的实时性。通过实验表明该算法能够快速准确地完成数字路标识别。
