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.