Salient Region Detection Based on Image Feature-Pair Distributions

• Main Authors: Huang, Wen-Chung, 黃文中
• Other Authors: Wang, Sheng-Jyh
• Format: Others
• Language: en_US
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/38316193603377295196

碩士 === 國立交通大學 === 電子工程系所 === 97 === In this thesis, we propose an algorithm for the detection of human visual saliency regions. Given an image, the proposed algorithm can automatically determine these locations where humans tend to pay more attention to. The image is first decomposed into three channels, including one intensity channel and two opponent-color channels. For each channel, a feature-pair distribution is created for saliency analysis, and the analysis result is mapped back to the spatial domain to identify visually salient regions. Beside the suppression of noise interference, a normalization stage is included to improve the performance of detection. As demonstrated in the experimental results, the proposed method can successfully identify visual saliency regions in human visual reception and, at the same time, filter out less crucial information.