
doi: 10.1109/das.2012.54
This paper presents a scalable algorithm for segmentation free logo retrieval in document images. The contributions include the use of the SURF feature for logo retrieval, a novel indexing algorithm for efficient retrieval and a method to filter results using the orientation of local features and geometric constraints. Results demonstrate that logo retrieval can be performed with high accuracy and efficiently scaled to a large datasets.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 32 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
