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A Prototype System using Lexical Chains for Web Images Retrieval Based on Text Description and Visual Features

机译:基于文字描述和视觉特征的词法检索网络图像原型系统

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Content Based Image Retrieval, in the current scenario has not been analyzed adequate in the existing system. Here, we implement a prototype system for web based image retrieval. The system is based on description of images by lexical chains which are extracted from text related images in a web page. In this paper, we provide Relevance Feedback (RF) techniques that aim to the real world user requirements. The relevance feedback techniques, based on image text description are expanded to support image retrieval by combining textual and visual features. All the feedback techniques are implemented and compared with precision and recall criteria. The experimental results prove that retrieval methods that makes use of both text and visual features achieve overall better results than methods based only on image?s text description.
机译:在当前情况下,基于内容的图像检索在现有系统中尚未得到足够的分析。在这里,我们为基于Web的图像检索实现了原型系统。该系统基于词法链对图像的描述,这些词法链是从网页中与文本相关的图像中提取的。在本文中,我们提供了针对实际用户需求的相关性反馈(RF)技术。基于图像文本描述的相关性反馈技术被扩展为通过结合文本和视觉特征来支持图像检索。所有反馈技术均已实现,并与精度和召回标准进行了比较。实验结果证明,同时利用文本和视觉特征的检索方法比仅基于图像文本描述的检索方法总体上效果更好。

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