基于弦中点Hough变换的椭圆检测方法

为了提高从图像中检测椭圆的效率和精度，利用椭圆中心平分经过中心的弦的性质，提出了
一种基于弦中点Hough变换（CMHT）的椭圆检测方法。引入内切椭圆的概念，基于椭圆上所有点的内切椭
圆必经过椭圆中心的事实，对图像中边缘像素点的有效分布进行了分析。通过黑白边缘图像的提取，建立
二维数组累加器，依照像素点分布扫描边缘图像，累加器计数，最后进行椭圆位置和参数的计算。该算法
与标准Hough变换（SHT）和三点随机Hough变换（RHT-3） 相比，具有更高的执行速度和检测精度，同时
对于颗粒噪声具有较强的抵抗能力。

Chord midpoint Hough transform based ellipse detection method

A new method called chord midpoint Hough transform (CMHT) was proposed to improve the efficiency and accuracy of ellipse detection in an image. This method is based on the fact that a chord passing through the center of an ellipse is divided into bisection. As a result, the term "inscribed ellipse" was introduced, and all inscribed ellipses of an ellipse must pass its center. The algorithm mainly consists of extracting black and white edge images, scanning the edge images according to the distribution of pixels, accumulating of 2D accumulator, and finally computing the ellipse's positions and other parameters. In comparison with other detection algorithms, such as standard Hough transform (SHT) and random 3 dots Hough transform (RHT-3), this algorithm has higher speed and detection accuracy.