1。将Canny边缘检测器应用于灰度图像，得到二值边缘图。
2。从边缘图中提取边缘轮廓，填补等高线上的空白。
三.计算每个轮廓的低曲率以保持所有真实的角，所有曲率的局部极大值被认为是初始角点。
4。使用自适应局部阈值来去除初始角点，以去除圆角。
5。角候选的角度进行评估，以消除任何虚假角落由于量化噪声和琐碎的细节。上述评价基于一个动态的支持区域，该区域根据其相邻的角候选对象进行更改。
6。轮廓线的端点被认为有附加的标准。(1. Apply the Canny edge detector to the grey level image and obtain a binary edge-map.
2. Extract the edge contours from the edge-map, fill the gaps in the contours.
3. Compute curvature at a low scale for each contour to retain all true corners.All of the curvature local maxima are considered as initial corner candidates.
4. Initial corner candidates are compared using an adaptive local threshold to remove the round corners.
5. The angles of corner candidates are evaluated to eliminate any false corners due to quantization noise and trivial details. The above evaluation is based on a dynamic region of support, which changes according to its adjacent corner candidates.
6. End points of contours are considered with an additional criterion.)