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Automatic Localization and Boundary Detection of Retina in Images Using Basic Image Processing Filters

机译:基本图像处理过滤器的图像中视网膜的自动定位和边界检测

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This paper proposes an automatic localization and boundary detection of retina images using basic filters to support ophthalmologists for detection and diagnoses eyes harmful diseases such as glaucoma and diabetic retinopathy accurately and diligently. The proposed system comprising three main phases including preprocessing, segmentation and detection phase. The preprocessing phase is used to enhance retinal image and to remove the noise of the retina image. The second phase is the segmentation for main parts of retinal image including optic disc, blood vessels, and fovea to extract their features. Optic disc is segmented using color intensity, the region of interest (ROI) is detected and morphological operations are applied to reduce search complexity. Also, fovea feature is extracted and the blood vessels tree is extracted from retinal image using line detection techniques. The third phase is the detection, in which identification and classifying whether the input image is left or right eye, to support ophthalmologists in identifying which eye is infected by the disease and to check it periodically. Basic image processing filters including average filter, median filter, spatial filter and morphological filter are used in all system phases. Moreover, a simple approach were used to detect left and right retinal fundus images. The proposed system is tested and evaluated using a subset of ophthalmologic images of the publically available DRIVE database.
机译:本文提出了使用基本过滤器的视网膜图像自动定位和边界检测,以支持眼科医生进行检测,并准确且孜孜不倦地诊断眼睛有害疾病,如青光眼和糖尿病视网膜病变。所提出的系统,包括三个主要阶段,包括预处理,分段和检测阶段。预处理阶段用于增强视网膜图像并去除视网膜图像的噪声。第二阶段是视网膜图像的主要部分的分割,包括视神经盘,血管和FOVEA,以提取它们的特征。光盘使用颜色强度进行分段,检测感兴趣区域(ROI)并应用形态操作以降低搜索复杂性。此外,提取FoVEA特征,并且使用线路检测技术从视网膜图像中提取血管树。第三阶段是检测,其中识别和分类输入图像是否左眼或右眼,以支持眼科医生鉴定疾病感染的眼睛并定期检查它。基本图像处理过滤器包括平均滤波器,中值滤波器,空间滤波器和形态过滤器在所有系统阶段使用。此外,使用简单的方法来检测左右视网膜眼底图像。使用公开可用的驱动器数据库的眼科图像的子集进行测试和评估所提出的系统。

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