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Shape, Color and Texture Based CBIR System Using Fuzzy Logic Classifier

机译:基于模糊逻辑分类器的形状,颜色和纹理CBIR系统

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摘要

The perfect image retrieval and retrieval time are the two major challenges in CBIR systems. To improve the retrieval accuracy, the whole database is searched based on many image characteristics such as color, shape, texture and edge information which leads to more time consumption. This paper presents a new fuzzy based CBIR method, which utilizes colour, shape and texture attributes of the image. Fuzzy rule based system is developed by combining color, shape, and texture feature for enhanced image recovery. In this approach, DWT is used to pull out the texture characteristics and the region based moment invariant is utilized to pull out the shape features of an image. Color similarity and texture attributes are extorted using customized Color Difference Histogram (CDH). The performance evaluation based on precision and BEP measures reveals the superiority of the proposed method over renowned obtainable approaches.
机译:完美的图像检索和检索时间是CBIR系统中的两个主要挑战。为了提高检索准确性,基于许多图像特征(例如颜色,形状,纹理和边缘信息)搜索整个数据库,这导致更多时间消耗。本文介绍了一种新的基于模糊的CBIR方法,它利用了图像的颜色,形状和纹理属性。基于模糊规则的系统是通过组合颜色,形状和纹理特征来开发的,以增强图像恢复。在这种方法中,DWT用于拉出纹理特性,并且基于区域的力矩不变地用于释放图像的形状特征。使用自定义色差直方图(CDH)嵌入颜色相似性和纹理属性。基于精确和BEP措施的性能评估揭示了所谓的可获得方法的提出方法的优越性。

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