{"title":"基于特征提取和BP神经网络的纹理分类算法","authors":"Tongyang Liu, Zongguo Liu, Guoqing Wu","doi":"10.12733/JICS20105651","DOIUrl":null,"url":null,"abstract":"In this paper, we apply the texture conception of natural language to the texture classiflcation, and classify the natural texture into ten classes. Basing on the above, we found a small image library of natural texture. In the thesis, we discuss the common means of texture feature extraction, and bring forward a speciflc algorithm for Gabor fllter. In order to validity of the feature extraction, we adopt the BP network as the classifler to carry out our experiments, which bring us satisfying results.","PeriodicalId":213716,"journal":{"name":"The Journal of Information and Computational Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Algorithm of Texture Classification Based on Feature Extraction and BP Neural Network\",\"authors\":\"Tongyang Liu, Zongguo Liu, Guoqing Wu\",\"doi\":\"10.12733/JICS20105651\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we apply the texture conception of natural language to the texture classiflcation, and classify the natural texture into ten classes. Basing on the above, we found a small image library of natural texture. In the thesis, we discuss the common means of texture feature extraction, and bring forward a speciflc algorithm for Gabor fllter. In order to validity of the feature extraction, we adopt the BP network as the classifler to carry out our experiments, which bring us satisfying results.\",\"PeriodicalId\":213716,\"journal\":{\"name\":\"The Journal of Information and Computational Science\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-04-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Journal of Information and Computational Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.12733/JICS20105651\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of Information and Computational Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12733/JICS20105651","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Algorithm of Texture Classification Based on Feature Extraction and BP Neural Network
In this paper, we apply the texture conception of natural language to the texture classiflcation, and classify the natural texture into ten classes. Basing on the above, we found a small image library of natural texture. In the thesis, we discuss the common means of texture feature extraction, and bring forward a speciflc algorithm for Gabor fllter. In order to validity of the feature extraction, we adopt the BP network as the classifler to carry out our experiments, which bring us satisfying results.