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Survey of texture based feature extraction for skin disease detection

机译:基于纹理特征提取的调查皮肤病检测

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Skin diseases are most common form of infections occurring in people of all ages. As the costs of dermatologists to monitor every patient is very high, there is a need for a computerized system to evaluate patient's risk of skin disease using images of their skin lesions. Many researchers have used different preprocessing, segmentation and classification techniques to determine whether a skin image suffers from diseases or not. Feature extraction is very important for predictive modeling applications. Feature extraction in image processing is a method of capturing visual content of images for indexing and retrieval. Primitive image features can be either general features, such as extraction of color, texture and shape or domain specific features. Texture based features are widely used in image analysis for medical diagnosis. This paper presents a comprehensive survey of texture based feature extraction for detection of skin diseases and proposes a system based on the findings.
机译:皮肤病是所有年龄段人中的最常见的感染形式。由于皮肤科医生的成本监测每个患者非常高,需要一种计算机化系统来评估患者使用皮肤病变的图像来评估患者皮肤病的风险。许多研究人员使用了不同的预处理,分段和分类技术来确定皮肤图像是否患有疾病。特征提取对于预测性建模应用非常重要。图像处理中的特征提取是捕获图像的视觉内容以进行索引和检索的方法。原始图像特征可以是一般功能,例如提取颜色,纹理和形状或域特定功能。基于纹理的特征广泛应用于医学诊断的图像分析。本文介绍了对纹理纹理特征提取的综合调查,用于检测皮肤病,并提出了一种基于调查结果的系统。

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