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Segmentation and grading of eczema skin lesions

机译:湿疹皮肤病变的分割和分级

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In this paper Eczema skin lesions are segmented and graded using image processing and analysis. For preprocessing adaptive light compensation and gamma correction has been used. The effect of color space normalization has been studied for lesion segmentation. K-means algorithm is used for segmentation. We have used RGB and CIELab color models; and their normalized I and II versions. The experimental results show that normalized color spaces give better segmentation results than the normal color spaces. Our proposed algorithm gives best segmentation accuracy of 84.6% for RGB normalized II color space for the G channel for adaptive light compensation. The grading accuracy for erythema is around 70%.
机译:在本文中,湿疹皮肤病变使用图像处理和分析进行分割和分级。为了进行预处理,使用了自适应光补偿和伽马校正。已经研究了颜色空间归一化对病变分割的影响。 K-均值算法用于分割。我们使用了RGB和CIELab颜色模型;及其标准化的I和II版本。实验结果表明,归一化色彩空间比常规色彩空间具有更好的分割效果。我们提出的算法为G通道的RGB归一化II颜色空间提供了84.6%的最佳分割精度,以实现自适应光补偿。红斑的定级准确度约为70%。

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