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首页> 外文期刊>Advances in Science, Technology and Engineering Systems >Melanoma detection using color and texture features in computer vision systems
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Melanoma detection using color and texture features in computer vision systems

机译:使用计算机视觉系统中的颜色和纹理特征检测黑素瘤

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All forms of skin cancer are becoming widespread. These forms of cancer, and melanoma in particular, are insidious and aggressive and if not treated promptly can be lethal to humans. Effective treatment of skin lesions depends strongly on the timeliness of the diagnosis: for this reason, artificial vision systems are required to play a crucial role in supporting the diagnosis of skin lesions. This work offers insights into the state of the art in the field of melanoma image classification. We include a numerical section where a preliminary analysis of some classification techniques is performed, using color and texture features on a data set constituted by plain photographies, to which no pre-processing technique has been applied. This is motivated by the necessity to open new horizons in creating self-diagnosis systems for accessible skin lesions, due also to a huge innovation of cameras, smartphones technology and wearable devices.
机译:各种形式的皮肤癌正在普及。这些形式的癌症(尤其是黑色素瘤)具有隐蔽性和侵略性,如果不及时治疗可能会对人类造成致命的伤害。皮肤病变的有效治疗在很大程度上取决于诊断的及时性:因此,需要人工视觉系统在支持皮肤病变的诊断中起关键作用。这项工作提供了对黑素瘤图像分类领域的最新技术的见识。我们包括一个数字部分,其中使用普通照片组成的数据集上的颜色和纹理特征对一些分类技术进行了初步分析,而没有应用任何预处理技术。这是由于在相机,智能手机技术和可穿戴设备的巨大创新下,必须为创建可访问的皮肤损伤的自我诊断系统开辟新的视野。

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