Image Retrieval Based on the Wavelet Features of Interest
Te-Wei Chiang, Tienwei Tsai, Yo-Ping Huang · 2006
This paper presents a content-based image retrieval method based on the discrete wavelet transform (DWT). Due to the superiority in multiresolution analysis and spatial-frequency localization, the DWT is used to extract wavelet features (i.e., approximations, horizontal details, vertical details, and diagonal details) at each resolution level. Based on the observation that the YUV color space is rather effective in terms of the extraction of color features, each image is first transformed from the standard RGB color space to the YUV space, and then each component (i.e., Y, U, and V) of the image is further transformed to the Wavelet domain. In the image database establishing phase, the wavelet coefficients of each image are stored; in the image retrieving phase, the system compares the most significant wavelet coefficients of the Y, U, and V components of the query image with those of the images in the database, coupled with the weight factors assigned by users, and find out the matches based on the users' interested features. Experimental results demonstrate the effectiveness of our system.