In this paper, a complete logo detection/ recognition system for document images is proposed. In the proposed system, first, a logo detection method is employed to detect a few regions of interest (logo-patches), which likely contain the logo(s), in a document image. The detection method is based on the piece-wise painting algorithm (PPA) and some probability features along with a decision tree. For the logo recognition, a template based recognition approach is proposed to recognize the logo which may present in every detected logo-patch. The proposed logo recognition strategy uses a search space reduction technique to decrease the number of template logo-models needed for the recognition of a logo in a detected logo-patch. The features used for search space reduction are based on the geometric properties of a detected logo-patch. Based on our experimentations on 1290 document images of Tobacco800 dataset, 99.31% of the logos were detected as logo-patches. Among the detected logo-patches 97.90% of logos were fairly recognized. Considering both logo detection and recognition results, 97.22% of the logos in the document images could truly be detected/recognized as the overall performance of the proposed system.
Conference proceeding
A complete logo detection/recognition system for document images
Proceedings of the 11th International Workshop on Document Analysis Systems, pp.324-328
Proceedings of the 11th International Workshop on Document Analysis Systems (Tours, France, 4-10 April)
2014
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Abstract
Details
- Title
- A complete logo detection/recognition system for document images
- Creators
- Ali Reza AlaeiM Delandre
- Publication Details
- Proceedings of the 11th International Workshop on Document Analysis Systems, pp.324-328
- Conference
- Proceedings of the 11th International Workshop on Document Analysis Systems (Tours, France, 4-10 April)
- Publisher
- IEEE; USA
- Number of pages
- 324-328
- Identifiers
- 2027; 991012822028902368
- Academic Unit
- Faculty of Science and Engineering; Information Technology; School of Business and Tourism; Faculty of Business, Law and Arts
- Resource Type
- Conference proceeding