低对比度下手机膜缺陷图像的分割研究

Image Segmentation for Mobile Phone Film Defects Under Low Contrast

针对低对比度下手机膜缺陷图像分割较难的问题,提出了一种改进的Retinex增强方法。首先,利用高斯卷积估计缺陷图像的光照分量,获取反射分量;对反射分量进行自适应非线性变换以及对比度受限自适应直方图均衡(CLAHE)修正,提高图像对比度,并利用顶帽变换进一步去除光照背景的影响,实现手机膜缺陷图像的增强。然后,针对最大类间方差(OTSU)算法对缺陷边缘的暗细节分割不完整的问题,引入增强图像的梯度图像,实现手机膜缺陷的有效分割。实验结果表明:在低对比度情况下,相较于原缺陷图像,本文算法处理后的图像的信息熵提升约20%,对比度提升约100%,分割效果较好。

Image segmentation is the focus of mobile phone film defect detection.However,the low contrast of captured images often makes image segmentation difficult.In this regard,this paper proposed an improved Retinex enhancement method.The method used Gaussian convolution to estimate the illumination component of defect image to obtain the reflection component,performed adaptive nonlinear transformation on the reflection component,employed contrast-limited adaptive histogram equalization(CLAHE)correction to improve the contrast,used the top-hat transform to eliminate the influence of lighting background,and enhanced the defect image of the mobile phone film.Then,aiming at the incomplete segmentation of the dark details of the defect edge by Otsu's algorithm,a gradient image of the enhanced image was introduced to achieve effective segmentation of mobile phone film defects images.The experimental results show that in the case of low contrast,compared with the original defect image,the image processed by this algorithm has an improved information entropy of about 20%,a contrast of about 100%,and an excellent segmentation effect.