Graph Edit Distance for Active Graph Matching in Content Based Retrieval Applications

Application of multimedia technologies to visual data, like still images and videos, is receiving an increasing attention especially for the large number of potential innovative solutions which are expected to emerge in the next years. In this context, techniques for retrieval by visual similarity are expected to boost the interest of users through the definition of novel paradigms to access digital repositories of visual data. In this paper, we define a novel model for active graph matching and describe its application to content based retrieval of images. The proposed solution fits with the class of edit distance based techniques and supports active node merging during the graph matching process. A theoretical analysis of the computational complexity of the proposed solution is presented and a prototype system is experimented on the images of two sample image collections.