拐点检测一直是计算机的视觉和图像处理中的关键问题，传统方法是通过计算曲率来实现拐点的检测，其要求准确定位拐点所在局部区域的位置，并易受到噪声干扰，为此提出了一种的新的基于形态骨架的快速拐眯检测方法，该方法基于物体条件骨架原理，采用改进的非对称开运算算子，并利用内外骨架分别实现对物体凸点和凹点的检测，以保证对拐点检测的完整性；对于有噪声图象，则采用多刻度形态滤波进行去噪预处理；对拐点给出了统一的检测和实现模型。实验结果表明，该统一算法检测准确度高、具有旋转不变性、计算量小、硬件实现简单，对有噪声干扰图象也能很好地进行检验。

Corner detection is an important task in various computer vision and image-understanding system. Traditional methods are based on chain-code and curvature computation of curves, which suffer the dependence either on the correctness of region segmentation or on the susceptivity of noise. In this paper, a novel corner detection method based on mathematical morphology is proposed, which is very different from traditional chain-code based corner detection methods. This method is based on morphological skeleton principle, and uses a modified opening operator to detect the convex and concave corner of the image. The result of the corner detection is achieved by compose the result of the two-corner sets of the source image and its complement set. The multi-scale morphological filter is used to eliminate noise. The uniform model of corner detection has also been established. Experiments show that this method leads to accurate detection, low computational cost, and rotational invariance.