Multiwavelet based Texture Features for Content based Image Retrieval

Content based image Retrieval has become one of the most active research areas in the past few years .CBIR system using multiwavelet based features with high retrieval rate and less computational complexity is proposed in this paper. Multiwavelets offer simultaneous orthogonality, symmetry and short support. This property made it a powerful tool for feature extraction of images in the database. A comparative study is done between multiwavelet feature vectors and wavelet feature vectors for 999 different texture images in a databank. Result analysis show that extracting texture information using multiwavelet provides significantly improved results in terms of retrieval accuracy, computational complexity and storage space of feature vectors as compared to wavelet based CBIR. Euclidean Distance and Canberra Distance are used as similarity measure in the proposed CBIR system.