Image Retrieval based on Integration between YCbCr Color Histogram and Texture Feature

Abstract

Content-Based Image Retrieval (CBIR) allows automatically extracting target images according to objective visual contents of the image itself. Content-based image retrieval has many application areas such as, education, commerce, military, searching, biomedicine and web image classification. This paper proposes a new image retrieval system, which uses color and texture information to form the feature vectors and Bhattacharyya distance and new similarity measure to perform the feature matching. This framework integrates the yc b c r color histogram which represents the global feature and edge histogram as local descriptor to enhance the retrieval results. The proposed technique is proper for precisely retrieving images even in deformation cases such as geometric deformations and noise. It is tested on a standard image databases such as Wang and UCID databases. Experimental work shows that the proposed approach improves the precision and recall of retrieval results compared to other approaches reported in literature.

A hybrid approach for Content-Based Image Retrieval based on Fast Beta Wavelet network and fuzzy decision support system

“…Other approaches were proposed for features selection and dimension reduction by using principal component analysis (PCA),wavelets, Ripplets and its derivations [14][15][16][17][18]. Others combined the visual content in order to increase the robustness and efficiency [19][20][21][22][23]. Also, Lande et al [24] presented an effective approach which combine color, texture and shape features based on the extraction of dominant color of each block, gray-level co-occurrence matrix (GLCM) and Fourier descriptors, respectively.…”

A Hybrid Data Dependent Dissimilarity Measure for Image Retrieval

“…Colour histograms as an important and useful tool for analyzing colour images that are invariant to rotation and translation are used in this work as image features. They carry the statistical information of the chosen colour space and have been used in several image retrieval research works [16][17][18][19][20][21][22].…”

A New Approach of Content Based Image Retrieval Using Color and Texture Features

“…Nowadays image retrieval system is a hot topic in digital image processing techniques from data mining community [1]. Digital images are rapidly growing because of developing techniques of multimedia and information.…”

“…Digital images are rapidly growing because of developing techniques of multimedia and information. The storage and transmission challenges are tackled by different image compression techniques [1]. The property of image may be lost or remain unchanged through this compression.…”