基于金字塔结构的层次霍夫变换

C. Espinosa, M. Perkowski
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引用次数: 8

摘要

描述了一种基于金字塔结构的分层霍夫变换,它是移动机器人中低空间视觉子系统的主要组成部分。系统中的处理顺序最初被认为是提取室内场景中线条特征的必要条件,包括:直方图均衡化,使用中间滤波器平滑,使用Sobel边缘检测器进行边缘检测,二值化提取检测到的边缘,标记,重新二值化和细化以将边缘细化为细线,以及使用HT方法的分层方法进行线条提取。我们的任务是确定每个步骤对分层式HT成功的重要性。它在一台基于386、内存为640k的个人计算机上实现,与标准的HT实现相比,得到了高质量的结果。
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Hierarchical Hough transform based on pyramidal architecture
A hierarchical Hough transform (HT) based on pyramidal architecture is described, being a main component of the low-to-medium spatial vision subsystem for a mobile robot. The sequence of processing in the system originally conceived to be essential to the extraction of line features in indoor scenes consisted of: histogram equalization, smoothing with the use of a medial filter, edge detection using the Sobel edge detectors, binarization to extract the edges detected, labeling, rebinarization and thinning to refine the edges to thin lines, and line extraction using a hierarchical approach to the HT method. The task was to establish the importance of each step for the success of the hierarchical HT. It was implemented on a 386-based personal computer with 640 K memory and proved to give results of high quality as compared with the standard HT implementation.<>
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