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A Circle Contour Measurement Technique Based on Randomized Hough Transform Using Gradient Information

机译:基于梯度信息的随机霍夫变换的圆轮廓测量技术

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摘要

Hough Transform (HT) is an image edge detection technique which is widely used in pattern recognition and computer vision. In this paper the fundamental principle of HT is analyzed and the defect of HT and Randomized Hough Transform (RHT) is indicated. An algorithm based on RHT and the information of grayscale and gradient in image is proposed. It uses the property of the pattern and is mainly used for detection of circle and arc contour measurement. This algorithm can decrease memory usage in computer by a multi to one mapping, accelerate the calculation speed by parallel algorithm, improve the edge detection accuracy by subpixel division, obtain the parameters of object by applying least square fitting algorithm. Based on the principle, a measurement system with high accuracy and efficiency in image capturing and processing is developed. Experiments are carried out in the system. The result of experiment has certified the feasibility and validity of the algorithm.
机译:霍夫变换(HT)是一种图像边缘检测技术,广泛用于模式识别和计算机视觉。本文分析了HT的基本原理,指出了HT的缺陷以及随机霍夫变换(RHT)的不足。提出了一种基于RHT和图像灰度梯度信息的算法。它利用图案的特性,主要用于检测圆弧和圆弧轮廓。该算法可以通过多对一映射减少计算机的内存使用量,通过并行算法加快计算速度,通过子像素划分提高边缘检测精度,通过应用最小二乘拟合算法获得物体的参数。基于该原理,开发了一种在图像捕获和处理中具有高精度和高效率的测量系统。实验是在系统中进行的。实验结果证明了该算法的可行性和有效性。

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