Wavelet Based Image Retrieval Method

A novel method for retrieving image based on color and texture extraction is proposed for improving the accuracy. In this research, we develop a novel image retrieval method based on wavelet transformation to extract the local feature of an image, the local feature consist color feature and texture feature. Once an image taking into account, we transform it using wavelet transformation to four sub band frequency images. It consists of image with low frequency which most same with the source called approximation (LL), image containing high frequency called horizontal detail (LH), image containing high frequency called vertical detail (HL), and image containing horizontal and vertical detail (HH). In order to enhance the texture and strong edge, we combine the vertical and horizontal detail to be other matrix. The next step is we estimate the important point called significant point by threshold the high value. After the significant points have been extracted from image, the coordinate of significant points will be used for knowing the most important information from the image and convert into small regions. Based on these significant point coordinates, we extract the image texture and color locally. The experimental results demonstrate that our method on standard dataset are encouraging and outperform the other existing methods, improved around 11 %. Keywords-component; Image retrieval; DWT; Wavelet; Local feature; Color; Texture.