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Features for Melanoma Lesions Characterization in Computer Vision Systems

机译:计算机视觉系统中黑色素瘤病灶特征的特征

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Computer vision systems are increasingly used for the early detection of skin diseases, such as malignant melanoma. The various proposals of computer vision systems are characterized by some fundamental common phases: image acquisition, pre-processing, segmentation, features extraction and selection and finally classification. In most of the related papers dealing with this topic, many features are extracted in order to feed classifiers from the simplest to the most sophisticated. Features are typically extracted using digital image processing methods (i.e., segmentation, edge detection and color and structure processing), and an open discussion about the meaning of these features and the objective ways of measuring them is ongoing. Therefore, the need to investigate this topic in order to find a guideline to support new researchers on these issues arises. The present work is a not exhaustive review of the most frequently used features in the elaboration of computer vision systems. The shortcomings in some of the existing studies are highlighted and suggestions for future research are provided.
机译:计算机视觉系统越来越多地用于早期发现皮肤病,如恶性黑素瘤。计算机视觉系统的各种建议的特征在于一些基本的常见阶段:图像采集,预处理,分割,特征提取和选择以及最终分类。在处理本主题的大多数相关论文中,提取了许多功能,以便从最简单到最复杂的最简单的分类器馈送分类器。通常使用数字图像处理方法(即,分割,边缘检测和颜色和结构处理)提取特征,以及关于这些特征的含义的开放讨论和测量它们的客观方式正在进行中。因此,需要调查本主题,以便找到支持这些问题的新研究人员的指导。目前的作品是对阐述计算机视觉系统中最常用的功能的不详尽综述。一些现有研究的缺点是突出显示的,并提供了未来研究的建议。

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