基于Hough变换和连通体分析的混合圆形体检测算法

A Hybrid Approach Based Hough Transform and Connected Component Analysis for Circular Objects Detection and Measurement

从复杂图像中准确可靠地检测圆形体是计算机视觉和智能化图像理解的关键技术之一.现存算法存在检测精度低,对噪声及复杂背景敏感等缺点.奉文提出一种新的混合算法.首先采用一种改进Hough变换获取参数空间并生成其横切面图像;然后对该横切面图像进行连通体分析,检测出圆形体的尺寸和中心位置.改进Hough变换重新定义了,掩模及积分算子;连通体分析则采用一种改进网形测度.大量实验表明所提算法具有更高检测率、检测精度和鲁棒性.

It is a key technique for computer vision and image understanding to detect and measure circular objects in images. Existing algorithms possess several drawbacks such as low detecting and measuring accuracies and poor robustness to image degradation. This paper proposes a two-stage hybrid approach to solve this problem. In the first stage, a modified Hough transform is used to obtain the accumulative space of the original image; in the second stage, connected components in the horizontal cross section image of the accumulative space are analyzed to extract those corresponding circular objects. Geometric parameters of the extracted connected components are scaled up to obtain the desired center coordinates and sizes of the circular objects. Results of experiments demonstrate that the proposed approach possesses higher performance than several existing ones.