A STUDY FOR STABLE CRACK SEGMENTATION REGARDLESS TEXTURE IN REVETMENT IMAGE.

Abstract

Convolutional Neural Networks are biased towards recognising textures. Thus, the accuracy is also reduced between images with different textures in crack Segmentation. In this study, We evaluated the difference of texture by calculating features of crack images. To make a model that can detect cracks more stably, we compared the performance of a model with only batch normalization and models contained instance normalization.