Color and Rotated M-Band Dual Tree Complex Wavelet Transform Features for Image Retrieval

Abstract

Abstract-In this paper, a novel algorithm which integrates the RGB color histogram and texture features for content based image retrieval. A new set of twodimensional (2-D) M-band dual tree complex wavelet transform (M_band_DT_CWT) and rotated M_band_DT_CWT are designed to improve the texture retrieval performance. Unlike the standard dual tree complex wavelet transform (DT_CWT), which gives a logarithmic frequency resolution, the M-band decomposition gives a mixture of a logarithmic and linear frequency resolution. Most texture image retrieval systems are still incapable of providing retrieval result with high retrieval accuracy and less computational complexity. To address this problem, we propose a novel approach for image retrieval using M_band_DT_CWT and rotated M_band_DT_CWT (M_band_DT_RCWT) by computing the energy, standard deviation and their combination on each subband of the decomposed image. To check the retrieval performance, two texture databases are used. Further, it is mentioned that the databases used are Brodatz gray scale database and MIT VisTex Color database. The retrieval efficiency and accuracy using proposed features is found to be superior to other existing methods.

Department of IT, GIT, GITAM University, Visakhapatnam

“…The corel-1k database consists of one thousand images of ten different classes of images; each class type consists of one hundred images. We have evaluated our proposed video indexing and retrieval algorithm on the video database available at [20]. The retrieval performance is evaluated using precision and recall.…”

“…Comparison of average precision and average recall results of proposed DLDBP and that of existing CS-LBP method are as shown in below graphs in figure, Our proposed video indexing and retrieval frameworks results are as shown below. As discussed above our proposed algorithm is applied on a video database of forty videos (airplane, sailing boat, car, and war tank), which are available at [20]. The average precision and average retrieval recall results of, video indexing and retrieval framework of key frame based DLDBP, for different numbers of top matches are as shown in the following graphs in figure Fig.…”

“…Experiments are carried out on benchmark image database Corel-1k and compared the results with existing central symmetric local binary patterns method. Also, we have evaluated the video indexing and retrieval framework on a database available at [20], and compared the results with the existing volume local binary patterns (VLBP) method. Compared to existing methods our proposed methods have shown reasonably good results.…”

“…Hadis Heidari et al [19] have introduced a method for image retrieval based on graphical processors units. K. Prasanthi Jasmine et al in [20] have introduced a new framework meant for image retrieval based on color and wavelet transform features. A new algorithm useful for medical image retrieval based on generalized gamma distribution is proposed in the paper [21].…”

A New Approach to Region Based Image Retrieval using Shape Adaptive Discrete Wavelet Transform

“…Also it is known that DWT is very fast computing transformation tool [9], hence most RBIR systems are based on wavelet and related wavelet coefficients. However, image retrieval approaches based on DWT, are not sensitive to edge singularities [10,11,12]. For this reason two alternatives are provided, one is using Gabor filters [13], and the other is using Curvelet transform [9].…”