Edge-based structural features for content-based image retrieval

This paper proposes structural features for content-based image retrieval (CBIR), especially edge/structure features extracted from edge maps. The feature vector is computed through a _"water-filling algorithm" applied on the edge map of the original image. The purpose of this algorithm is to efficiently extract information embedded in the edges. The new features are more generally applicable than texture or shape features. Experiments show that the new features can catch salient edge/structure information and improve the retrieval performance.