Image Semantic Segmentation Based on Texture Element Block Recognition and Merging
Xu Yang · Jisuanji gongcheng · 2015
Aiming at the problem that the current image semantic segmentation algorithm at pixel level is difficult to use global shape features,leading the fuzzy contour of object and some wrong recognitions. This paper presents a new regional level image semantic segmentation algorithm based on texture element block recognition and merging. This algorithm uses the texture element feature to segment objects with a clear outline,which fully considers the relationship between adjacent pixels and keeps corners and edge information between objects. Experiments conducted on the MSRC database show that this method can segment and recognize a variety of semantic. Besides,it has the advantages of high efficiency,high recognition rate and good segmentation effect.