基于改进的Hough变换图像分割方法

在图像处理和计算机视觉中,Hough变换是一种应用非常广泛的图像边缘检测技术,针对传统Hough变换算法所需的存储容量大、计算量大、速度慢、效率低,不能确定曲线端点及长度的问题,提出了一种改进的Hough变换方法,它根据Hough变换思想的逆变换,采用对参数空间逐步细分的方法,逐步排除不包含直线的区域,能够有效地减少存储容量,提高运行效率,并能有效地求出曲线轮廓的端点及长度.该方法已成功运用于车牌自动识别系统的车牌分割中.

Study of image segmentation based on improved Hough transform

Hough transform has been widely used in pattern recognition and computer vision since its discovery,but it cannot detect the endpoints and length of a curve. Furthermore, high memory space is required in traditional Hough transform. In this paper, an improved Hough transform algorithm is proposed. According to the inverse transform of HT,it subdivides image space little by little and excludes the area without lines. With this algorithm,the memory space required is reduced, and high efficiency is available, besides the endpoint and length of a curve can be detected. It has been applied to the vehicle license plate recognition (LPR) system successfully.