{"title":"Content based image retrieval using enhanced Gabor wavelet transform","authors":"Anusha Yalavarthi, K. Veeraswamy, K. Sheela","doi":"10.1109/COMPTELIX.2017.8003990","DOIUrl":null,"url":null,"abstract":"Nowadays content-based image retrieval (CBIR) is the most powerful and popular method for retrieving color, shape, and texture. In this paper, we proposed content based image retrieval using enhanced Gabor wavelet transform for increasing the retrieval efficiency. Gabor wavelet transform (GWT) is widely concentrated on the combination of features of plane wave and Gabor function to form non-orthogonal functions. The challenge property of the training database images using GWT is decomposed into different scaling and orientation with different filters to reduce the unwanted information of the images. The proposed experimental results of the Gabor wavelet transform give excellent results in terms of retrieval efficiency also computational rates as compared to existing techniques.","PeriodicalId":6917,"journal":{"name":"2017 International Conference on Computer, Communications and Electronics (Comptelix)","volume":"6 1 1","pages":"339-343"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Computer, Communications and Electronics (Comptelix)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMPTELIX.2017.8003990","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
Nowadays content-based image retrieval (CBIR) is the most powerful and popular method for retrieving color, shape, and texture. In this paper, we proposed content based image retrieval using enhanced Gabor wavelet transform for increasing the retrieval efficiency. Gabor wavelet transform (GWT) is widely concentrated on the combination of features of plane wave and Gabor function to form non-orthogonal functions. The challenge property of the training database images using GWT is decomposed into different scaling and orientation with different filters to reduce the unwanted information of the images. The proposed experimental results of the Gabor wavelet transform give excellent results in terms of retrieval efficiency also computational rates as compared to existing techniques.