A NEW DESCRIPTOR BASED ON 2D DCT FOR IMAGE RETRIEVAL

Cong Bai (1) , Kidiyo Kpalma (1) , Joseph Ronsin (1)

1 IETR - Institut d'Électronique et des Technologies du numéRique

Content-based image retrieval relies on feature comparison between images. So the selection of feature vector is important. As many images are compressed by transforms, constructing the feature vector directly in transform domain is a very popular topic. We propose a new feature vector in DCT domain. Our method selects part of DCT coefficients inside each block to construct AC-Pattern and use DC coefficients between neighboring blocks to construct DC-Pattern. Two histograms are formed and parts of them are used to build a descriptor vector integrating features to do image retrieval. Experiments are done both on face image databases and texture image database. Compared to other methods, results show that we can get better performance on both face and texture database by using the proposed method.

Keywords: CBIR; DCT; face recognition; texture retrieval

Domains: Signal and Image processing; Signal and Image Processing

Cong Bai, Kidiyo Kpalma, Joseph Ronsin. A NEW DESCRIPTOR BASED ON 2D DCT FOR IMAGE RETRIEVAL. International Conference on Computer Vision Theory and Applications (VISAPP), Feb 2012, Rome, Italy. 4 p. ⟨hal-00728076⟩