肤色检测技术综述

肤色检测在人脸和手势识别与跟踪、Web图像内容过滤、数据库或因特网中的人物检索和医疗诊断等方面有广泛应用,文中通过分别介绍基于统计和基于物理的两类肤色检测技术,较全面地综述了肤色检测技术,其中对颜色空间选择、静、动态肤色建模方法、肤色反射模型和肤色波谱特性等肤色检测重要环节做了分析,明确了选择颜色空间与特征提取和分类方法的联系,强调了研究肤色波谱特征对基于物理的肤色检测技术的重要性,最后探讨了肤色检测的技术难题和发展趋势。     

基于CbCgCr椭球体似然平滑度的肤色分割

对于有色偏、高光和阴影的复杂背景彩色人脸图像,已有模型不能获得较理想的分割结果。为此,提出一种基于CbCgCr椭球体肤色似然平滑度的肤色分割算法。预处理人脸输入图,以消除色偏、高光和阴影,建立CbCgCr椭球体肤色模型,计算肤色似然平滑度,利用肤色似然平滑度粗分割肤色区域,并对其进行去噪处理,以获得肤色细分割图和细提取图。实验结果表明,对光照不均和背景复杂的人脸彩色图像,该算法的肤色分割准确性、鲁棒性和实时性较优。     

猪皮对球形弹丸阻滞作用的仿真研究

为了明确皮肤对球形弹丸的阻滞作用机理,建立了模拟皮肤的 3 层结构模型。基 于拉伸及压缩力学特性曲线,利用 MATLAB 对皮肤模型进行参数识别。基于冲击实验得到的 皮肤穿透阈值速度验证了皮肤模型的准确性。利用 LS-DYNA 仿真模拟了 Φ4.5 mm 铅球侵彻皮 肤过程,从球形弹丸速度衰减、皮肤鼓包方面分析了皮肤对球形弹丸的阻滞作用。仿真模拟了 相同动能不同密度条件下,直径为 Φ4.5 mm 的弹丸侵彻皮肤的过程和相同动能不同直径条件 下,铅球侵彻皮肤的过程,结果表明,建立的皮肤 3 层结构模型可以用于模拟皮肤的真实伤害, 作为皮肤的数值仿真模型;在初始动能相同的情况下,球形弹丸密度越小,体积越大,能量耗 散比越大,皮肤阻滞作用越明显,为后续研究投射物对真实人体的伤害奠定了基础。     

基于比例特征的网络不良图像过滤算法研究

目前对网络不良图像进行过滤的方法中,裸露肤色比依然是常被利用的数据,但是其存在一些缺陷,如伪肤色的干扰、非关键区域肤色的干扰、整体裸露肤色比有时候不与裸露程度呈正相关等。本算法利用人体肤色的一致性和人体结构特点,计算了以下三个比例特征作为判决依据——人脸尺寸占比、用人脸肤色数据改进肤色模型后的整体裸露肤色比及人体关键区域的裸露肤色比,有效地解决了上述问题;同时,对人脸检测增加了合适的旋转图像的处理过程,使其对于倾斜很大的人脸也能较好地检测。经过测试,算法的识别率达到91.5%,基本能满足实际应用的需求。     

A robust incremental learning framework for accurate skin region segmentation in color images

In this paper, we propose a robust incremental learning framework for accurate skin region segmentation in real-life images. The proposed framework is able to automatically learn the skin color information from each test image in real-time and generate the specific skin model (SSM) for that image. Consequently, the SSM can adapt to a certain image, in which the skin colors may vary from one region to another due to illumination conditions and inherent skin colors. The proposed framework consists of multiple iterations to learn the SSM, and each iteration comprises two major steps: (1) collecting new skin samples by region growing; (2) updating the skin model incrementally with the available skin samples. After the skin model converges (i.e., becomes the SSM), a post-processing can be further performed to fill up the interstices on the skin map. We performed a set of experiments on a large-scale real-life image database and our method observably outperformed the well-known Bayesian histogram. The experimental results confirm that the SSM is more robust than static skin models.     

Skin detection for single images using dynamic skin color modeling

Up-to-date skin detection techniques use adaptive skin color modeling to overcome the varying skin color problem. Most methods for tracking skin regions in videos utilize the correlation between contiguous frames. This paper proposes a new approach for detecting skin in a single image. This approach uses a local skin model to shift a globally trained skin model to adapt the final skin model to the current image. Experimental results show that the proposed method can achieve better accuracy. Two improvements for speeding up the processing are also discussed.     

彩色人体图像的二值化方法

为了快速有效的对彩色人体图像进行二值化处理,提出了一种新的自适应二值化处理方法.该方法根据人体肤色特征,建立人体肤色模型;根据该模型,分割出肤色和非肤色,再直接转换成二值图像.由于人体肤色受到不同光照和环境的影响,人体彩色图像中的人体肤色值会有偏移.为了改善肤色模型适应不同环境和光照,在肤色分割过程中,采用了自适应Gamma校正方法.最后,给出了该方法的实验结果.实验结果表明,提出的彩色人体图像的二值化方法快速且有效.     

虚拟的“真实”——交互动画中仿真蒙皮的探索

柔性蒙皮的皮肤不像刚性蒙皮那么僵硬,本文的目的就在于将长期应用于传统影视动画制作中的柔性蒙皮技术移植到交互领域中,即改变目前应用于交互领域中的角色几何体及其动画信息的数据结构,重新塑造一种信息文件的结构方式,使得在实时骨骼蒙皮的过程中,皮肤顶点受骨骼的影响值不会受到限制,达到真正意义上的柔性节点蒙皮,从而为交互状态下的角色动画提供一种新的动画解决方案。     

Integration of modified ABCD features and support vector machine for skin lesion types classification

Multimedia Tools and Applications - The abnormal growth of skin cells often leads to skin cancer due to the exposure of skin cells to the sun. The skin disease is primarily caused by bacteria,...     

基于边缘跟踪方法的肤色区域检测

常用的肤色模型只针对肤色的颜色信息,在较复杂的光照情况下检测效果不理想。为此,结合肤色在HSV颜色空间的分布特点以及肤色区域的边缘信息,提出一种应用于肤色区域检测的边缘跟踪方法。实验结果表明,该方法能准确检测图像中的肤色区域,检测结果优于传统的肤色模型,且对侧光、阴影等具有较好的鲁棒性。     

一种快速、鲁棒的人脸检测方法

根据特征脸思想，提出了一种新的基于特征肤色的人脸检测方法。首先从RGB彩色空间转换到HSI彩色空间中，然后训练肤色点样本集得到特征肤色，最后在特征肤色构成的肤色空间中检测人脸，实验表明，该方法是快速的，鲁棒的。     

Image specific discriminative feature extraction for skin segmentation

In recent times, the majority of colour-based skin detection methods used skin modelling in different colour spaces, and they are capable of skin classification at a pixel level. However, the accuracy of these methods is significantly affected by different issues, such as the presence of skin-like colours in scene background, variations in skin pigmentation, scene illumination, etc. Recent developments show that the discriminating power of a colour-based skin classifier can be increased by employing texture and spatial features. However, we observed that discriminability between skin and non-skin regions does not follow any statistics, and the discrimination is extremely image specific. In this paper, a novel adaptive discriminative analysis (ADA) is proposed to extract most discriminant features between skin and non-skin regions from an image itself in an unsupervised manner. Experimental results for standard databases show that the proposed method can efficiently segment out skin pixels in the presence of skin-like background colours.

     

A Hyperspectral Space of Skin Tones for Inverse Rendering of Biophysical Skin Properties

We present a method for estimating the main properties of human skin, leveraging a hyperspectral dataset of skin tones synthetically generated through a biophysical layered skin model and Monte Carlo light transport simulations. Our approach learns the mapping between the skin parameters and diffuse skin reflectance in such space through an encoder-decoder network. We assess the performance of RGB and spectral reflectance up to 1 μm, allowing the model to retrieve visible and near-infrared. Instead of restricting the parameters to values in the ranges reported in medical literature, we allow the model to exceed such ranges to gain expressiveness to recover outliers like beard, eyebrows, rushes and other imperfections. The continuity of our albedo space allows to recover smooth textures of skin properties, enabling reflectance manipulations by meaningful edits of the skin properties. The space is robust under different illumination conditions, and presents high spectral similarity with the current largest datasets of spectral measurements of real human skin while expanding its gamut.     

人体面部皮肤检测分析系统设计

设计了一种人体面部皮肤检测分析系统,在采用高清皮肤摄像头获取脸部皮肤图片的基础上,结合图像处理和智能信息处理技术实现了对面部皮肤的粗糙度、纹理度、光泽度、水份、弹性、色泽等6个指标及皮肤质量综合评价.该系统运用C屿Matlab混合编程技术,具有友好的交互界面,能够帮助消费者实时、便捷、客观地了解脸部皮肤状态,给出专业的护肤建议,具有广阔的应用前景.     

Adaptive skin color modeling using the skin locus for selecting training pixels

Techniques for color-based tracking of faces or hands often assume a static skin model yet skin color, as measured by a camera, can change when lighting changes. Therefore, for robust skin pixel detection, an adaptive skin color model must be employed. We demonstrate a chromaticity-based constraint to select training pixels in a scene for updating a dynamic skin color model under changing illumination conditions. The method makes use of the ‘skin locus’ of a camera, that is, the area in chromaticity space where skin chromaticity under various lighting and camera calibration conditions is observed. Skin color models derived from the technique are compared with that derived by a common spatial constraint and is shown to be more consistent with manually extracted ground truth skin model per frame even as localization errors increase. The technique is applied to color-based face tracking in indoor and outdoor videos and is shown to succeed more often than other color model adaptation techniques.     

Hybrid Human Skin Detection Using Neural Network and K-Means Clustering Technique

Human skin detection is an essential step in most human detection applications, such as face detection. The performance of any skin detection system depends on assessment of two components: feature extraction and detection method. Skin color is a robust cue used for human skin detection. However, the performance of color-based detection methods is constrained by the overlapping color spaces of skin and non-skin pixels. To increase the accuracy of skin detection, texture features can be exploited as additional cues. In this paper, we propose a hybrid skin detection method based on YIQ color space and the statistical features of skin. A Multilayer Perceptron artificial neural network, which is a universal classifier, is combined with the k-means clustering method to accurately detect skin. The experimental results show that the proposed method can achieve high accuracy with an F₁-measure of 87.82% based on images from the ECU database.     

三维虚拟人皮肤变形技术分类及方法研究

在虚拟人合成研究领域,皮肤变形一直是一个重要和活跃的研究方向．首先概略介绍三维人体几何表示方法以及皮肤的表示和几何建模方法,然后针对目前存在的皮肤变形方法,提出了两重分类方法．首先按照三维人体几何表示方法将皮肤变形分成两大类：表面模型皮肤变形和多层模型皮肤变形,然后按照皮肤变形机制把表面模型皮肤变形方法分成4个子类．详细介绍了每类方法的原理和优缺点,最后指出了皮肤变形目前存在的问题并展望了未来的发展方向．     

运用自适应球体模型实现肤色动态分割

提出一种用于变化光照、多姿态和复杂背景条件下人脸识别的肤色区域动态分割算法。对彩色人脸输入图进行色偏校正和亮度调节预处理,利用肤色聚类特性构建一种自适应球体肤色模型,并基于该模型计算自适应肤色相似度,利用肤色相似度,采用自适应的动态阈值进行肤色区域目标的分割和提取。实验结果表明,对于变化光照、多姿态和复杂背景的彩色人脸图像,该算法有良好的分割精度和自适应性。     

鲁棒的肤色检测方法

肤色检测常用的方法有颜色空间阈值法,肤色统计模型和基于分割的方法.然而,上述方法对于光照不好的图片往往得不到很好的效果,而且在背景颜色与肤色相近时,往往误判背景为肤色.为此,提出了一个综合的方法,它对图片光照和背景颜色具有鲁棒性:先作图像预处理,通过阈值法选出肤色像素,再对肤色密度分布进行估计,最后使用改进的分水岭算法进行肤色区域生长.实验结果表明,该方法可以有效降低背景颜色的干扰,提高了肤色轮廓的精确度.     

基于支持向量机的肤色检测

根据支持向量机理论和肤色信息分布特点,提出用支持向量机方法进行肤色检测.在YCbCr、YIQ、YUV颜色空间中,去除照度分量,分别以各像素点的色度向量为输入,用像素点所属类别--皮肤区域与非皮肤区域为输出,建立各颜色空间的支持向量机肤色检测器.实验表明,该方法具有良好的肤色检测效果.