Automatic Segmentation of Exudates in Retinal Images

S. Bharkad
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引用次数: 1

Abstract

This paper presents a new technique for segmentation of exudates in fundus images. This technique is based on Discrete Wavelet Transform (DWT) and histogram based thresholding procedure. In this work, Optic Disc (OD) is eliminated using DWT from original green component image prior segmentation of exudates. This step aids to avoid the misclassification of exudates region. Histogram based threshold calculation procedure is introduced for segmentation of bright regions in green component image. Hard exudates are obtained after masking the OD region in segmented bright regions of the green component image. This technique was evaluated on images from DIARETDB0 and DIARETDB1 databases. The average sensitivity, specificity and accuracy achieved by proposed method are 0.7890, 0.9972 and 0.9964 respectively. Comparison with existing methods offered in the literature shows that the performance of proposed approach is significant.
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视网膜图像中渗出物的自动分割
提出了一种新的眼底图像中渗出物的分割方法。该技术基于离散小波变换(DWT)和基于直方图的阈值处理。在这项工作中,使用DWT从原始绿色分量图像中去除视盘(OD)。这一步骤有助于避免对渗出区域的错误分类。介绍了一种基于直方图的阈值计算方法,用于绿色分量图像中明亮区域的分割。在绿色分量图像的分割亮区中,对OD区进行掩码处理,得到硬渗出物。该技术在DIARETDB0和DIARETDB1数据库的图像上进行了评估。该方法的平均灵敏度、特异性和准确度分别为0.7890、0.9972和0.9964。与文献中已有方法的比较表明,本文提出的方法具有显著的性能。
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