Efficient logo retrieval through hashing shape context descriptors
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
A polar-based logo representation based on topological and colour features
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
Document seal detection using GHT and character proximity graphs
Pattern Recognition
Scalable triangulation-based logo recognition
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
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Graphics detection and recognition are fundamental research problems in document image analysis and retrieval. As one of the most pervasive graphical elements in business and government documents, logos may enable immediate identification of organizational entities and serve extensively as a declaration of a document's source and ownership. In this work, we developed an automatic logo-based document image retrieval system that handles: 1) Logo detection and segmentation by boosting a cascade of classifiers across multiple image scales; and 2) Logo matching using translation, scale, and rotation invariant shape descriptors and matching algorithms. Our approach is segmentation free and layout independent and we address logo retrieval in an unconstrained setting of 2-D feature point matching. Finally, we quantitatively evaluate the effectiveness of our approach using large collections of real-world complex document images.