Color image retrieval using geometric properties
In this paper, we present a novel region-based color image retrieval system using geometric properties. First, a region-growing technique is employed to cluster the connected color pixels with the same color in an image to form color regions, which are the primitive elements in our proposed approach. In the feature extraction module, two important descriptive geometry features are extracted, the spatial relational graph (SRG) and the Fourier description coefficients (FDCs) of each color region. In the matching module, relational distance graph matching between two SRGs is performed to find the best matches with the minimum relational distance. Then, shape matching is applied to obtain the best match with the minimum geometric distance. In our work, the method proposed by Cinque [1] is modified to perform the relational distance graph matching, then the wavelet transform is applied to extract the critical points on the contour of color regions. Experimental results reveal the feasibility of our proposed approach in solving the color image retrieval problem.
image retrieval shape matching wavelet transform maximin algorithm hungarian method