为了能够快速、精确地检测出矩形,综合分析目前存在的矩形检测算法的优缺点,提出了一种快速、高精度的矩形检测算法。所提算法首先采用环形窗口将图像分割为多个感兴趣区域,再提取感兴趣区域的亚像素轮廓,并将亚像素轮廓分割为若干线段,然后利用模糊数学理论对线段的几何和物理特性进行融合计算,最终根据模糊融合得到的判决结果完成矩形的高精度检测和定位。实验结果表明:所提算法的检测速度是基于Hough变换的矩形检测算法的7.4倍,检测最大中心定位误差为(0.507 pixel,0.272 pixel);长度的平均误差为1.034 pixel,宽度的平均误差为1.310 pixel,倾角的平均误差为0.304°,并且能够准确地检测出矩形。所提算法满足工业应用中快速、高精度的要求,且有较强的稳定性。

To quickly and accurately detect rectangles and comprehensively analyze the advantages and disadvantages of existing rectangle detection algorithms, a fast and high-precision rectangle detection algorithm is proposed herein. The proposed algorithm first divides an image into multiple regions of interest using a ring window, then extracts the subpixel contour of the region of interest, divides the subpixel contour into several line segments, and finally uses fuzzy mathematics to analyze the geometric and physical characteristics of the line segments. As a result of the fusion calculations, high-precision detection and positioning of the rectangle are obtained based on the fuzzy fusion assessment. Experimental results show that the detection speed of the proposed algorithm is 7.4 times that of the rectangle detection algorithm based on Hough transform, and the maximum center positioning error is (0.507 pixel, 0.272 pixel). Furthermore, the average length error is 1.034 pixel, the average width error is 1.310 pixel, and the average inclination error is 0.304°. The rectangle can be accurately detected through the proposed algorithm that meets the requirements of fast and high precision in industrial applications and exhibits strong stability.