Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/45300
Title: Logo recognition for mobile advertisement
Authors: Chen, Qing.
Keywords: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Issue Date: 2011
Abstract: This Final Year Project report covers the theoretical background, exploration of various aspects, and performance analysis of a logo recognition system which targets to enable mobile advertisement application. Two techniques were proposed to address the prominent problem of background noise. The project was based on the Bag-of-Words framework where each image is modeled as a collection of features. To simulate the user scenarios that users are to capture the logo images with mobile devices centered at the logo and placed right on top, the database construction follows certain criteria. Two databases were constructed in the project, one preliminary database for initial exploration and one final database of 30 logo subjects for system performance analysis. The selection of feature extraction technique for BoW framework, keypoint or dense sampling, was also discussed. A logo recognition scheme called Keypoint Match Ranking was developed to facilitate understanding of the robustness of BoW framework, especially SIFT descriptor and classifier.
URI: http://hdl.handle.net/10356/45300
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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