基于Windows平台的皮肤阻抗检测系统设计

提出了一种新型的皮肤阻抗检测系统。该系统硬件上采用AD620仪表放大器进行前置放大,并用基于USB 2.0的MP425 A/D采集卡进行数据采集;软件上采用Visual C＋＋.Net 2005开发平台进行软件程序开发,实现对信号的实时采集与处理,并将测量结果进行显示、存储和打印。该系统主要用于通过检测皮肤阻抗来找到经穴的位置,具有操作简单、实时测量、显示直观和管理方便等优点,不仅可满足实验的需要,同时具有一定的市场前景。     

基于Windows的多路阵列皮肤阻抗检测系统设计

该检测系统可以实时采集体表正方形区域上多点的阻抗信号,得到各点的阻抗值及各点间的阻抗差值关系,从而可以应用在研究针灸刺激等特定条件下人体阻抗分布变化问题。可以提供单路检测系统无法提供的信息。多路阵列测量系统第一次将皮肤阻抗的检测由“点”扩展为“面”,在小规模实验取得了较好的结果,其具有检测效率高、操作简单、实时测量、显示直观和管理方便等优点。不仅可用于中医临床实验,且具有一定的市场前景。 该系统硬件上采用基于USB2．0的A／D采集卡进行数据采集;软件上采用基于Windows的Visual C＋＋．Net2005开发平台进行软件程序开发,实现对信号的实时采集与处理,并将测量结果在计算机屏幕上进行实时的直观显示、存储和打印。     

基于Windows平台的皮肤阻抗检测系统设计

提出了一种新型的皮肤阻抗检测系统.该系统硬件上采用 AD620仪表放大器进行前置放大,并用基于USB 2.0的MP425 A/D采集卡进行数据采集;软件上采用Visual C .Net 2005开发平台进行软件程序开发,实现对信号的实时采集与处理, 并将测量结果进行显示、存储和打印.该系统主要用于通过检测皮肤阻抗来找到经穴的位置,具有操作简单、实时测量、显示直观和管理方便等优点,不仅可满足实验的需要,同时具有一定的市场前景.     

基于windows的皮肤阻抗检测系统

利用经络的皮肤低电阻特性,研究科学地检测经络的方法,从检测皮肤阻抗的方法出发进行分析,为检测经络提供了一种实践依据.介绍一个基于windows的皮肤阻抗检测系统,讨论在检测皮肤阻抗的方法中,该系统选择探测法的原因.利用该系统进行一系列的检测,探讨由该系统得出的实验结果.该系统可以很好地检测到中医理论中经络的准确位置.     

皮肤阻抗微机检测系统的原理与设计

皮肤阻抗微机检测系统是实时测量皮肤阻抗的变化。该系统对临床针灸准确寻找经脉穴位及提高针刺疗效提供了科学的方法，本文主要介绍其工作原理及软件的开发过程。     

基于图像传感器的皮肤纹理自动测量系统设计

为了客观定量评价皮肤纹理的老化,介绍了一种基于图像传感器的皮肤纹理自动测量系统。首先,利用CMOS图像传感器在光照条件下通过光电转换实现对皮肤图像的采集。然后,借助图像处理技术对采集的图像进行处理。最后,用软件定量计算皮肤表面纹理中的各测量指标（如,皮嵴的平均面积、数量、皮沟的深度等）,并在此基础上通过统计学方法来分析各个测量指标的特点。整个系统集采集、处理与计算于一体,具有低功耗、高稳定、应用性广、操作简单等优点。     

基于AD5933的无线多通道微型阻抗测量系统设计与试验研究

阻抗测量芯片AD5933具有集成度高、成本低等优点，具备解决结构损伤识别领域中阻抗仪体积大、成本昂贵等问题的潜力。然而，目前研究中基于AD5933的阻抗测量评估板或开发板，均存在数据传输距离短、测量通道单一、需人工值守等问题，给实际工程应用带来诸多不便。为此，本文研制出了一种以AD5933芯片为核心，集成无线通信模块、多通道自动切换模块等，具备无线数据传输、多通道多测点采集、远程数据后处理功能的微型阻抗测量采集分析系统，通过与有线阻抗测量装置的阻抗测量效果对比试验，验证了所研制系统无线测量方案的可行性和测量结果的准确性，通过实验室管道模型的多螺栓服役状态监测试验，验证了所研制系统多通道多测点阻抗测量的优势和适用性。     

一种有效的皮肤检测算法

肤色特征是人体表面的重要特征,在人脸检测与识别、基于内容的不良图像过滤系统中有着重要的地位。分析了YUV颜色空间系统的特点,提出了一种基于椭圆区域的皮肤模型,将该模型应用于基于内容的不良图像过滤系统的皮肤检测部分中。实验表明,利用该模型进行皮肤检测能够达到很好的效果。     

人体皮肤对药物吸收的检测研究

简单介绍了采用光声光谱技术检测人体皮肤对稀土皮肤药物的吸收，研究了药物渗透皮肤的扩散作用，作者以氩离子激光为光辐射源，用声光调制器进行强度调制，通过选择调制频率，设计制作适用的光声池等措施检测系统具有高的灵敏度，提高了信噪比，从而用锁定放大器有效地提取的微弱信号。     

多通道皮肤听声系统中语音增强算法的应用研究

针对提高应用多通道皮肤听声系统进行语音识别的识别率,提出了基于多频带谱减法的语音增强算法。在多通道皮肤听声的实验中,有色噪声会严重降低语音质量,进而降低皮肤听声系统语音识别的识别率,因而首次将基于多带谱减法的语音增强算法引入到皮肤听声系统中以降低有色噪声。多频带谱减法将语音频带划分为多个子频带,分别在每个子频带作不同系数的谱减运算实现语音增强。通过Matlab完成了算法仿真并通过DSP硬件实现了算法并将增强后的语音信号输出给皮肤听声系统,实验证明此设计能够有效抑制有色噪声,增强皮肤听声系统的可靠性和实用性。     

一种与局部模型相结合的自适应肤色检测方法

使用预先训练得到的肤色高斯模型进行肤色检测,容易受到环境影响。为了提高肤色检测的性能和精度,提出一种与局部模型相结合的自适应肤色模型检测方法。在YCgCr颜色空间中使用高斯模型对图像进行肤色分割,并利用初次检测到的肤色区域像素数据建立局部模型,估计出模型参数。把局部模型与预先训练得到的参数相结合,得到自适应的肤色模型。实验表明,该方法和单独的肤色高斯模型相比,提高了在不同背景和光照下肤色检测正确率。     

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.     

Approximation by skin surfaces

We present a method to approximate a simple, regular C² surface W in by a (tangent continuous) skin surface S. The input of our algorithm is a set of approximate W-maximal balls, where the boundary of the union of these balls is homeomorphic to W. By generating patches of spheres and hyperboloids over the intersection curves of the balls the algorithm determines a one-parameter family of skin surfaces, where a parameter controls the size of the patches. The skin surface S is homeomorphic to W, and the approximate W-maximal balls in the input set are also S-maximal. The Hausdorff distance between the regions enclosed by the input surface W and the approximating skin surface S depends linearly on a parameter related to the sampling density of the approximate W-maximal balls.     

基于肤色与肤色矩实时视频人脸检测与跟踪

提出了一种新颖、鲁棒、实时人脸检测与跟踪算法.该方法采用背景差分法提取运动区域,对运动区域利用肤色归一化RGB和HSV色彩模型的聚类性,得到人脸候选区域.利用人脸几何信息和孔洞信息对人脸候选区域进行验证.基于肤色矩特性,对人脸区域进行跟踪与预测.通过对不同背景条件下的人脸检测与跟踪,实验结果表明,所提算法不仅检测率高,且对光照,人脸姿态的变化具有较强的鲁棒性.基于480×360图像处理速度平均为25帧/秒,可满足系统实时性要求.     

Color based skin classification

Skin detection is used in applications ranging from face detection, tracking body parts and hand gesture analysis, to retrieval and blocking objectionable content. In this paper, we investigate and evaluate (1) the effect of color space transformation on skin detection performance and finding the appropriate color space for skin detection, (2) the role of the illuminance component of a color space, (3) the appropriate pixel based skin color modeling technique and finally, (4) the effect of color constancy algorithms on color based skin classification. The comprehensive color space and skin color modeling evaluation will help in the selection of the best combinations for skin detection. Nine skin modeling approaches (AdaBoost, Bayesian network, J48, Multilayer Perceptron, Naive Bayesian, Random Forest, RBF network, SVM and the histogram approach of Jones and Rehg (2002)) in six color spaces (IHLS, HSI, RGB, normalized RGB, YCbCr and CIELAB) with the presence or absence of the illuminance component are compared and evaluated. Moreover, the impact of five color constancy algorithms on skin detection is reported. Results on a database of 8991 images with manually annotated pixel-level ground truth show that (1) the cylindrical color spaces outperform other color spaces, (2) the absence of the illuminance component decreases performance, (3) the selection of an appropriate skin color modeling approach is important and that the tree based classifiers (Random forest, J48) are well suited to pixel based skin detection. As a best combination, the Random Forest combined with the cylindrical color spaces, while keeping the illuminance component outperforms other combinations, and (4) the usage of color constancy algorithms can improve skin detection performance.     

The secret of velvety skin

Asperity scattering adds a 'surface lobe' to the usual diffuse, backscatter, and specular lobes of rough surfaces. Although rarely acknowledged, it is an important effect in many materials that are covered with a thin layer of sparse scatterers, such as dust or hairs. In common cases where single scattering predominates, asperity scattering adds important contributions to the structure of the occluding contour and the edge of the body shadow. This is because the bidirectional reflectance distribution function (BRDF) is inversely proportional to the cosines of both the illumination and viewing angles. The BRDF is generally low (and typically negligible) except when either the illuminating rays or visual directions graze the surface. Because asperity scattering selectively influences the edges in the image of an object, it has (as judged by photometric magnitudes) a disproportionally large effect on (human) visual appreciation. We identify it as a neglected but often decisive visual cue in the rendering of human skin. Its effect is to make smooth cheeks look 'velvety' or 'peachy', that is to say, soft (the appearances of both velvet and peachy skin are dominated by asperity scattering). This is a most important aesthetic and emotional factor that is lacking in Lambertian (looks merely dullish and paper-like), 'skin-type' BRDF (looks like glossy plastic), or even translucent (looks 'hard', vitreous) types of rendering.Published online: 8 August 2003     

光照自适应的肤色检测方法

通过在颜色空间YCgCr里对不同光照环境下的肤色特征进行研究,发现不同光照环境下的肤色像素高度聚集在不同的Cg、Cr区域。对此,提出了利用相关矩阵法对图片的光照环境进行估计,然后针对图片的光照环境检测结果采用不同的肤色分割方法,并采用一种基于类间方差和类内离散度相结合的动态阈值方法来确定分割阈值。该方法与传统的肤色检测方法相比,能够充分减少不同光照环境下带来的颜色失真的影响,是一种光照自适应的肤色检测方法。实验表明,该方法对肤色检测具有较高的准确率和较低的误检率。     

IC-integrated flexible shear-stress sensor skin

This paper reports the successful development of the first IC-integrated flexible MEMS shear-stress sensor skin. The sensor skin is 1 cm wide, 2 cm long, and 70 /spl mu/m thick. It contains 16 shear-stress sensors, which are arranged in a 1-D array, with on-skin sensor bias, signal-conditioning, and multiplexing circuitry. We further demonstrated the application of the sensor skin by packaging it on a semicylindrical aluminum block and testing it in a subsonic wind tunnel. In our experiment, the sensor skin has successfully identified both the leading-edge flow separation and stagnation points with the on-skin circuitry. The integration of IC with MEMS sensor skin has significantly simplified implementation procedures and improved system reliability.     

Data fusion for skin detection

Two methods of data fusion to improve the performance of skin detection were tested. The first method fuses two chrominance components from the same color space, while the second method fuses the outputs of two skin detection methods each based on a different color space. The color spaces used are the normalized red, green, blue (RGB) color space, referred to here as pixel intensity normalization, and a new method of obtaining the R, G, and B components of the normalized RGB color space called maximum intensity normalization. The multilayer perceptron (MLP) neural network and histogram thresholding were used for skin detection. It was found that fusion of two chrominance components gives a lower skin detection error than a single chrominance component regardless of the database or the color space for both skin detection methods. In addition, the fusion of the outputs of two skin detection methods further reduces the skin detection error. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008