Genetic approach based image retrieval by using CCM and textual features

P. Shrivas, U. Lilhore, Nitin Agrawal
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引用次数: 1

Abstract

As the quantity of web clients are expanding every day. This work concentrate on the retrieval of pictures by using the visual and annotation characteristics of the images. In this work two kind of features are utilized for the bunching of the picture dataset. So Based on the comparability of content and CCM components of the picture bunches are made. For bunching here genetic approach is utilized. Two phase learning genetic algorithm named as teacher learning based optimization was utilized for clustring. Here client pass two kind of queries first was content while other is image, this assistance in choosing suitable cluster for retrieval of picture. Analysis was done on genuine and artificial set of pictures. Result demonstrates that proposed work is better on various assessment parameters as contrast with existing strategies.
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基于CCM和文本特征的遗传图像检索方法
随着网络客户端的数量每天都在扩大。这项工作主要是利用图像的视觉特征和注释特征来检索图像。在这项工作中,两种特征被用于图像数据集的聚类。因此,基于内容和CCM的可比性,对图片进行了分组。这里的聚束采用遗传方法。采用基于教师学习的两阶段学习遗传算法对聚类进行优化。客户端通过两种查询,一种是内容查询,另一种是图像查询,这有助于选择合适的聚类进行图像检索。对真品和仿品进行了分析。结果表明,与现有的评估策略相比,本文所提出的工作在各评估参数上都有较好的效果。
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