Unconstrained logo detection in document images |
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Authors: | Tuan D. Pham |
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Affiliation: | School of Computing and Information Technology, Griffith University, Nathan Campus, Brisbane, Qld. 4111, Australia |
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Abstract: | A fast and effective algorithm is developed for detecting logos in grayscale document images. The computational schemes involve segmentation, and the calculation of the spatial density of the defined foreground pixels. The detection does not require training and is unconstrained in the sense that the presence of a logo in a document image can be detected under scaling, rotation, translation, and noise. Several tests on different electronic document forms such as letters, faxes, and billing statements are carried out to illustrate the performance of the method. |
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Keywords: | Logo detection Document imaging Segmentation Mountain function |
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