Paper
7 February 2011 Automatic picture orientation detection based on classifier combination
Author Affiliations +
Proceedings Volume 7879, Imaging and Printing in a Web 2.0 World II; 78790C (2011) https://doi.org/10.1117/12.880046
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States
Abstract
Automatic picture orientation recognition is of great significance in many applications such as consumer gallery management, webpage browsing, content-based searching or web printing. We try to solve this high-level classification problem by relatively low-level features including Spacial Color Moment (CM) and Edge Direction Histogram (EDH). An improved distance-based classification scheme is adopted as our classifier. We propose an input-vector-rotating strategy, which is computationally more efficient than several conventional schemes, instead of collecting and training samples for all four classes. Then we research on the classifier combination algorithm to make full use of the complementarity between different features and classifiers. Our classifier combination methods include two levels: feature-level and measurement-level. And we present two classifier combination structures (parallel and cascaded) at measurement-level with a rejection option. As the precondition of measurement-level methods, the theory of Classifier's Confidence Analysis (CCA) is introduced with the definition of concepts such as classifier's confidence and generalized confidence. The classification system finally approached 90% recognition accuracy on a wide unconstrained consumer picture set.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yuejia Sun, Changsong Liu, Xiaoqing Ding, Zhigang Fan, and Francis Tse "Automatic picture orientation detection based on classifier combination", Proc. SPIE 7879, Imaging and Printing in a Web 2.0 World II, 78790C (7 February 2011); https://doi.org/10.1117/12.880046
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Cited by 2 scholarly publications.
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KEYWORDS
Curium

Feature extraction

Distance measurement

Classification systems

Printing

Simulation of CCA and DLA aggregates

Statistical analysis

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