In this paper, a new approach to the image retrieval problem is presented, that uses Edge Potential Functions (EPF) and genetic algorithms (GA). The method allows a user to draw a rough sketch of the shape and to find or rank the images in a database that contain a similar shape at any position, rotation and scaling factor. It will be explained how GAs allow to exploit the capability of EPFs to attract a sketch contour: as a result, the algorithm provides the set of geometrical transformations corresponding to the best match, and a confidence factor about the presence of a matching object. The method has been widely tested achieving very satisfactory results.
Edge potential functions and genetic algorithms for shape-based image retrieval
Dao, Minh Son;De Natale, Francesco;Massa, Andrea
2003-01-01
Abstract
In this paper, a new approach to the image retrieval problem is presented, that uses Edge Potential Functions (EPF) and genetic algorithms (GA). The method allows a user to draw a rough sketch of the shape and to find or rank the images in a database that contain a similar shape at any position, rotation and scaling factor. It will be explained how GAs allow to exploit the capability of EPFs to attract a sketch contour: as a result, the algorithm provides the set of geometrical transformations corresponding to the best match, and a confidence factor about the presence of a matching object. The method has been widely tested achieving very satisfactory results.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione



