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Classification of red blood cells disease using fuzzy logic theory

机译:基于模糊逻辑理论的红细胞疾病分类

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摘要

Blood cell classification is the initial process for detecting diseases; the diseases can be carried if it is detected at early stage. For solving such problems. Quantitative processing of digital images based on fuzzy technique is applied for classification of red blood cells. There are various features consist of shape, size and colour based features that based on statistical analysis (i.e. Mean, Standard Deviation, Variance, Roundness, Skewness, Kurtosis) have been extracted. The classification results indicated that these features highly signification and can be used for classification of red cells to the normal and up normal cells. The obtained result successfully identified 98% of red blood cells.
机译:血细胞分类是检测疾病的初始过程。如果在早期发现,可以携带疾病。用于解决此类问题。将基于模糊技术的数字图像量化处理应用于红细胞分类。已经提取了基于形状,大小和颜色的各种特征,这些特征是基于统计分析(即均值,标准偏差,方差,圆度,偏度,峰度)提取的。分类结果表明,这些特征具有很高的意义,可用于将红细胞分类为正常细胞和正常细胞。获得的结果成功鉴定出98%的红细胞。

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