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| Salient Building Region Detection for Scene Classification |
| CHEN Shuo, YU Xiao-Sheng, WU Cheng-Dong, CHEN Dong-Yue |
| (College of Information Science and Engineering, Northeastern University, Shenyang 110819, China) |
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Abstract In order to achieve outdoor scene classification in urban areas quickly, an effective method for detecting salient building region based on visual attention selection mechanism was proposed. Firstly, eightdirectional Gabor filter is used to obtain horizontal-vertical enhanced image. Secondly, salient building candidate regions are extracted through mapping from salient map which is constructed by phase Fourier tranform to the enhanced image. Finally, an orientation histogram discrimination algorithm is used to eliminate interference target, and salient building region detection is completed by CV model segmentation. The method extracts the building regional information which can represent scene based on PFT and orientation features, it effectively improves the real-time of algorithm and the capability of scene analysis, and implements the accurate detection of region in pixel level. The results of experiments with the university of Southern California outdoor scene database show that the method performs well in the detection result, computational speed and robustness.
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Received: 22 April 2011
Published: 30 August 2011
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