Image retrieval based on the directional edge similarity

This paper introduces a new shape based image retrieval scheme. This scheme employs the image edge directional similarity in generating the feature vector. The previous comparable schemes consider the point edge angles without any regard for its neighboring point edges. Those schemes offer some advantages such as translation, scaling and rotation invariant. Their problems are high sensitivity to false edges or high computational barrier, and lack of considering spatial domain correlation in feature vector components. This new scheme has all the advantages of previous scheme, because it employs the edges point angles, but overcomes their drawbacks with considering the point edge directional similarity. This scheme uses two factors in producing the feature vector which improves the retrieval effectivity: the edge point angle and amplitude, and its relation with the its neighboring edge points.. This scheme is robust against noise, since noise has little effect on similar directional edges, consequently there is no need to do any extra computation to identify the false edges. This results in low computational cost of this scheme in comparison with other similar schemes.