A Model of Visual Attention for Natural Image Retrieval

Guanghai Liu, D. Fan
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引用次数: 40

Abstract

In this paper, saliency textons model is proposed to encode color, orientation and saliency cue and spatial information as image features for CBIR, where the image representation is so called saliency textons histogram. Experimental results indicate that the performances of saliency textons histogram outperform Gabor filter and multi-text on histogram. The saliency textons histogram can combine color feature, edge feature and spatial layout together. Furthermore, saliency textons model can simulate visual attention mechanism.
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自然图像检索中的视觉注意模型
本文提出了显著性文本模型,将颜色、方向、显著性线索和空间信息编码为CBIR的图像特征,其中图像表示称为显著性文本直方图。实验结果表明,显著性文本直方图的性能优于Gabor滤波和多文本直方图。显著性文本直方图可以将颜色特征、边缘特征和空间布局结合在一起。此外,显著性文本模型可以模拟视觉注意机制。
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