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Towards automatic acne detection using a MRF model with chromophore descriptors

机译:使用带有生色团描述符的MRF模型实现自动痤疮检测

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This paper proposes a new acne detection approach using a Markov random field (MRF) model and chromophore descriptors extracted by bilateral decomposition. Compared to most existing acne segmentation methods, the proposed algorithm enables to cope with large-dynamic-range intensity usually existing in conventional RGB acne images captured under uncontrolled environment. Algorithm performance has been tested on acne images of human face from a free public database. Experimental results show that acne segmentation derived from this new approach highly agrees to human visual inspection. Moreover, inflammatory response and hyperpigmentation scar can be well discriminated. It is expected that a computer-assisted diagnostic system for acne severity evaluation will be constructed as a consequence of the present work.
机译:本文提出了一种新的痤疮检测方法,使用马尔可夫随机场(MRF)模型和通过双边分解提取的生色团描述符。与大多数现有的痤疮分割方法相比,该算法能够应对在不受控制的环境下捕获的常规RGB痤疮图像中通常存在的大动态范围强度。已经对来自免费公共数据库的人脸痤疮图像进行了算法性能测试。实验结果表明,从这种新方法派生的痤疮分割与人体视觉检查高度吻合。此外,可以很好地区分炎症反应和色素沉着疤痕。期望作为本工作的结果,将构建用于痤疮严重性评估的计算机辅助诊断系统。

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