Abstract
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.
Original language | English |
---|---|
Title of host publication | 2014 IEEE International Conference on Image Processing, ICIP 2014 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 2998-3002 |
Number of pages | 5 |
ISBN (Electronic) | 9781479957514 |
DOIs | |
State | Published - 28 Jan 2014 |
Externally published | Yes |
Publication series
Name | 2014 IEEE International Conference on Image Processing, ICIP 2014 |
---|
Bibliographical note
Publisher Copyright:© 2014 IEEE.
Keywords
- Sketch based image retrieval
- orientation histograms
- sketch descriptors