A Content-Based Image Retrieval system using Visual Attention

Gulsah Tumuklu Ozyer, F. Vural
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引用次数: 3

Abstract

Semantic gap, difference between visual features and semantic annotations, is an important problem of Content-Based Image Retrieval (CBIR) systems. In this study, a new Content-Based Image Retrieval system is proposed by using Visual Attention which is a part of human visual system. In the proposed work, the region of interests are extracted by using Itti-Koch visual attention model. The attention values, obtained from the saliency maps are used to define a new similarity matching method. Successful results are obtained compared to traditional region-based retrieval systems.
基于内容的视觉注意图像检索系统
语义缺口,即视觉特征与语义注释之间的差异,是基于内容的图像检索(CBIR)系统的一个重要问题。本研究提出了一种新的基于内容的图像检索系统,该系统利用了人类视觉系统的一部分视觉注意。本文采用Itti-Koch视觉注意模型提取感兴趣区域。利用显著性图得到的关注值定义了一种新的相似度匹配方法。与传统的基于区域的检索系统相比,该方法取得了较好的效果。
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