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Colour normalization of fundus images based on geometric transformations applied to their chromatic histogram

机译:基于几何变换应用于其色直直方图的基底图像颜色标准化

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The high variability in fundus image databases is an important limiting drawback for detecting some retinal pathologies automatically. Age, human retinal pigmentation or lighting conditions affects in the colour of the acquired images. In this paper a colour-normalization method is presented as an initial pre-processing step in order to reduce the heterogeneity of retinal databases. The proposed method is based on geometric transformations applied to the chromaticity diagram of a target image taking into account a reference image. With the aim of quantifying the effect of the proposed colour normalization, a bright lesion detection from pathological images is carried out. A home-made system based on texture analysis and Support Vector Machine classification is used for this purpose. An improvement around a three percent in the detection accuracy demonstrates the importance of a retinal image colour pre-processing before any specific analysis.
机译:眼底图像数据库的高可变性是自动检测一些视网膜病理的重要限制缺点。年龄,人的视网膜色素沉着或照明条件影响所获得的图像的颜色。在本文中,将颜色归一化方法作为初始预处理步骤呈现,以降低视网膜数据库的异质性。所提出的方法基于考虑参考图像的目标图像的色度图的几何变换。随着量化提出的颜色归一化的效果的目的,进行了从病理图像的明亮病变检测。基于纹理分析和支持向量机分类的自制系统用于此目的。在检测精度中的三个百分之左右的改进证明了在任何特定分析之前的视网膜图像颜色预处理的重要性。

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