融合注意力机制的金属缺陷图像分割方法

由于金属表面缺陷图像的特性,有效精确分割是图像处理任务中的一大挑战.为了获得缺陷的类型、大小及位置信息,本文提出一种融合注意力机制的金属缺陷图像分割网络.该网络分为两条路径,语义信息路径主要由残差块构成的卷积网络获得特征图,采样过程中分步融合注意力机制以增强特征与背景对比度.旁路路径设计注意力机制模块获得位置信息的权重...

Metal defect image segmentation algorithm combined with attention mechanism

Due to the characteristics of metal surface defect images,effective an d accurate segmentation is a major challenge in image processing tasks.In order to obtain defect type,size and location information,this paper proposes a met al defect image segmentation network that incorporates attention mechanism.The network is divided into two paths.The semantic information path is mainly compo sed of a convolutional network composed of residual blocks to obtain a feature m ap.During the sampling process,the attention mechanism is integrated step by s tep to enhance the contrast between the feature and the background.The side roa d path design attention mechanism module obtains the weight map of the location information,and then combines the feature map of the same size with the weight map,and combines multi-scale features through the spatial pyramid.Experimenta l results show that the algorithm can improve the segmentation accuracy of metal surface defect images.