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Improving Performance of Image Retrieval Based on Fuzzy Colour Histograms by Using Hybrid Colour Model and Genetic Algorithm

机译:混合颜色模型和遗传算法提高基于模糊彩色直方图的图像检索性能

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摘要

A hybrid colour model is a colour descriptor formed by combining channels from several different colour models. Although rarely used in computer graphics applications due to redundancy, hybrid colour models may be of interest for the Content-Based Image Retrieval (CBIR). Best features of each colour model can be combined to obtain optimal retrieval performance. This paper evaluates several approaches to the construction of a hybrid colour model that is used to construct a fuzzy colour histogram of image as a compact feature for retrieval. By evaluating each channel separately, a colour model named HSY is proposed. Various parameters of fuzzy histogram are further improved using Genetic algorithm (GA). Using standard data sets and the Average Normalized Modified Retrieval Rank (ANMRR) as a metric for retrieval performance, it is shown that this novel approach can give an improved retrieval performance.
机译:混合颜色模型是通过组合来自几种不同颜色模型的通道而形成的颜色描述符。尽管由于冗余而很少在计算机图形应用中使用,但是混合颜色模型对于基于内容的图像检索(CBIR)可能是令人感兴趣的。可以组合每种颜色模型的最佳功能以获得最佳检索性能。本文评估了几种构建混合颜色模型的方法,该模型用于构建图像的模糊颜色直方图,作为检索的紧凑特征。通过分别评估每个通道,提出了一种名为HSY的颜色模型。使用遗传算法(GA)进一步改善了模糊直方图的各种参数。使用标准数据集和平均归一化修改后的检索等级(ANMRR)作为检索性能的指标,表明该新颖方法可以提供改进的检索性能。

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