基于机器视觉的手机屏幕表面划痕检测研究

针对手机屏幕图像划痕缺陷形状不规则、深浅对比度低的问题，提出基于机器视觉的手机屏幕表面划痕检测方法。首先采用PatMax算法和仿射变换对手机屏幕图像进行预处理；然后采用剪切变换将图像分解成低频和高频两部分，构造0°、45°、90°和135°四种方向的元素形状对低频部分进行灰度闭运算操作，同时对高频部分进行N×M中值滤波去噪处理，通过剪切逆变换生成增强图像；最后采用改进的Otsu双阈值方法对目标进行提取。随机选取450张手机屏幕图像进行实验，检测率最高可达98.7%，结果表明，该方法能够有效增强图像的细节信息，相比其他方法，极大地保证了划痕缺陷的完整性。

Surface scratch detection of mobile phone screen based on machine vision

Aiming at the problem of irregular shape and low contrast of the scratches in the image of mobile phone screen, a method based on machine vision was proposed to detect the surface scratches of mobile phone screen. Firstly, the PatMax algorithm and affine transformation were adopted to preprocess the screen images of mobile phone. Then the shear transformation was used to decompose the image into two parts: low frequency and high frequency, the element shapes in four directions of 0°, 45°, 90° and 135° were constructed to perform gray-scale closing operation on the low frequency part, and the N × M median filter denoising operation was performed on the high frequency part, the enhanced image was generated by the inverse shear transformation. Finally, the improved Otsu double threshold method was used to extract the target. 450 pieces of mobile phone screen images were randomly selected for experiments, and the highest detection rate is 98.7%. The results show that this method can effectively enhance the detail information of the images, which greatly guarantees the integrity of the scratch defects.