针对工业产品中非规则形状检测方法少、检测效率低的现状，本文提出了一种基于图像处理的快速高效检测方法。该方法首先对实际拍摄图像与参考模型进行特征点匹配，通过匹配寻找两幅图像中轮廓位置的映射关系，进而求解实际拍摄图像到参考模型的透视变换参数；然后对实际拍摄图像中的非规则形状进行高精度边缘提取，利用求取的透视变换参数对提取的边缘点进行变换；最后将计算得到的数据与参考图像中的数据进行比较，以此进行非规则形状检测。该方法为非接触式，设备少，环境影响小，数据对象仅是摄影图像，检测速度快，适用于各种非规则形状。标准实验分析表明，该方法检测精度优于0.2 mm，具有较高的检测精度及较好的检测效率。

In view of the current situation that the detection method is inefficient and low efficiency, this paper proposes a fast and efficient detection method for irregular shape. In this method, matching feature points between the actual captured image and the reference model are firstly used to find the contour mapping of the location, thereby solve their perspective transformation parameters. Then, extract edge of the irregular shape in the target image and transform the extracted edge points using the perspective transformation parameters. Finally, compared with the data, this method, non-contact, less equipment, low environmental impact, object is only the photographic image, and fast detection speed is suitable for all kinds of irregular shape. Standard experimental analysis shows that the method has high detection precision with 0.2 mm and good efficiency.