Sketch based image retrieval using a soft computation of the histogram of edge local orientations (S-HELO)

This paper introduces S-HELO (Soft-Histogram of Edge Local Orientations), an outperforming method for describing images in the context of sketch based image retrieval (SBIR). This proposal exploits the advantages provided by the HELO descriptor for describing sketches, and improves significantly its performance by using a soft computation of local orientations and taking into account spatial information. We experimentally demonstrate that a soft computation process together with a local estimation of orientations are very suitable for describing sketches in the context of image retrieval. Indeed, our results show that S-HELO significantly outperforms not only HELO but also classical orientation-based descriptors as HOG. We also show that S-HELO performs very close to the optimal when what we want to retrieve are target images. Moreover, our proposal also shows an outstanding performance for similarity search, i.e., retrieving images that belong to the same category of the query sketch.