Within the Content Based Image Retrieval (CBIR) framework, one of the main challenges is to tackle the scalability issues. We propose a new compact signature for similarity search. We use an original method to perform a high compression of signatures while retraining their effectiveness. We propose an embedding method that maps large signatures into a low-dimensional hilbert space. We evaluated the method on Holidays database and compared the results with methods of state-of-the-art.