Skip to Main Content
In this paper, we present a novel approach for improving retrieval accuracy based on DCT (discrete cosine transform) Filter-bank. First, we perform DCT on a given image, and generate a Filter-bank using the DCT coefficients for each color channel. In this step, DC and the limited number of AC coefficients are used. Next, a feature vector is obtained from the histogram of the quantized DC coefficients. Then, AC coefficients in the Filter-bank are separated into three main groups indicating horizontal, vertical, and diagonal edge directions, respectively, according to their spatial-frequency properties. Each directional group creates its histogram after employing Otsu binarization technique. Finally, we project each histogram on the horizontal and vertical axes, and generate a feature vector for each group. The computed DC and AC feature vectors are concatenated, and it is used in the similarity checking procedure. In order to evaluate the proposed scheme, state-of-art approaches including DC-based and DC and AC energy-based retrieval systems are implemented and compared in terms of retrieval accuracy. Experimental results show that the proposed algorithm outperforms the other approaches.