While the problem of Content Based Image Retrieval (CBIR) and automated image indexing systems has been widely studied in the past years they still represent a challenging research field. Indeed capturing high level semantics from digital images basing on low level basic descriptors remains an issue. A review of existing systems shows that edge descriptors are among the most popular features. While color features have led to extensive work, edge features haven't produced such active research and most current systems rather rely on completing basic edge information with other, more computationally expensive features such as texture. In this paper we propose to work on a more accurate edge feature while keeping a relatively low computation cost.