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首页> 外文期刊>Pattern Recognition: The Journal of the Pattern Recognition Society >Fast detection of facial wrinkles based on Gabor features using image morphology and geometric constraints
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Fast detection of facial wrinkles based on Gabor features using image morphology and geometric constraints

机译:使用图像形态和几何约束基于Gabor特征快速检测面部皱纹

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Facial wrinkles are important features of aging human skin which can be incorporated in several image-based applications related to aging. Facial wrinkles are 3D features of skin and appear as subtle discontinuities or cracks in surrounding skin texture. However, facial wrinkles can easily be masked by illumination/acquisition conditions in 2D images due to the specific nature of skin surface texture and its reflective properties. Existing approaches to image-based analysis of aging skin are based on the analysis of wrinkles as texture and not as curvilinear discontinuity/crack features. Previously, we proposed a stochastic approach based on Marked Point Processes (MPP) to localize facial wrinkles as curves. In this paper, we present a fast deterministic algorithm based on Gabor filters and image morphology to improve localization results. We propose image features based on Gabor filter bank to highlight the subtle curvilinear discontinuities in skin texture caused by wrinkles. Then, image morphology is used to incorporate geometric constraints to localize curvilinear shapes of wrinkles at image sites of large Gabor filter responses. Experiments are conducted on two sets of low and high resolution images and results are compared with those of MPP modeling. Experiments show that the proposed algorithm not only is significantly faster than MPP-based approach but also provides visually better results. (C) 2014 Elsevier Ltd. All rights reserved.
机译:面部皱纹是衰老的人类皮肤的重要特征,可以纳入与衰老相关的多种基于图像的应用中。面部皱纹是皮肤的3D特征,在周围的皮肤纹理中表现为细微的不连续或裂缝。但是,由于皮肤表面纹理的特殊性质及其反射特性,脸部皱纹很容易被2D图像中的照明/获取条件掩盖。现有的基于图像的衰老皮肤分析方法基于对皱纹的分析,而不是作为曲线的不连续/裂纹特征。以前,我们提出了一种基于标记点过程(MPP)的随机方法来将面部皱纹定位为曲线。在本文中,我们提出了一种基于Gabor滤波器和图像形态学的快速确定性算法,以提高定位效果。我们提出基于Gabor滤波器组的图像特征,以突出由皱纹引起的皮肤纹理中细微的曲线不连续性。然后,将图像形态学用于合并几何约束,以在大的Gabor滤波器响应的图像位置处定位皱纹的曲线形状。对两组低分辨率和高分辨率图像进行了实验,并将结果与​​MPP建模的结果进行了比较。实验表明,所提出的算法不仅比基于MPP的方法快得多,而且在视觉上效果更好。 (C)2014 Elsevier Ltd.保留所有权利。

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