A skin tone detection algorithm for an adaptive approach to steganography

Challenges face biometrics researchers and particularly those who are dealing with skin tone detection include choosing a colour space, generating the skin model and processing the obtained regions to fit applications. The majority of existing methods have in common the de-correlation of luminance from the considered colour channels. Luminance is underestimated since it is seen as the least contributing colour component to skin colour detection. This work questions this claim by showing that luminance can be useful in the segregation of skin and non-skin clusters. To this end, here we use a new colour space which contains error signals derived from differentiating the grayscale map and the non-red encoded grayscale version. The advantages of the approach are the reduction of space dimensionality from 3D, RGB, to 1D space advocating its unfussiness and the construction of a rapid classifier necessary for real time applications. The proposed method generates a 1D space map without prior knowledge of the host image. A comprehensive experimental test was conducted and initial results are presented. This paper also discusses an application of the method to image steganography where it is used to orient the embedding process since skin information is deemed to be psycho-visually redundant.     

汉语语音声调提取技术方法研究

随着现代科技和计算机以及平板电脑等的发展,语音交互将成为人机通信的主要方式,而汉语在语音合成中声调是不可或缺的一个重要组成部分。在声调提取过程中首先采用改进的短时自相关函数的方法进行基音检测,同时为了能较为精确地进行浊音的基音检测,利用变长分帧的方法提取基音周期序列,并通过Matlab仿真得到了汉语语音4种声调的调型曲线。仿真结果表明,该方法所得到的调型曲线与汉语普通话声调的典型曲线较为一致。     

A structural approach of pattern recognition

After defining the usual terms, a Pattern Recognition problem is stated as the linking of a representation to an interpretation. A basic knowledge is (dis)similarity measures. It is shown how the structure of the interpretation space conditions the law on this measure: usually both are homomorphic. We review the application of these ideas to clustering, hierarchies and first level recognitions, to statistical PR, to the fuzzy set approach, to information measures and even to logical statement interpretations.     

A reliable and unobtrusive approach to display area detection for imperceptible display camera communication

Object framework detection has been extensively studied in computer vision for applications such as document digitization and whiteboard scanning. Similarly, it is essential for display-camera communication systems, particularly when imperceptible data modulation is employed to enable simultaneous video playback and data transmission. Reliable and accurate localization of the encoded display area is critical for data demodulation and decoding. However, existing systems typically adapt established methods developed for other applications that do not meet the system requirements for high-rate data transmission.In this article, we propose a novel method for display area detection in the camera images by embedding a new localization marker into the display corners. While the localization marker is less obtrusive than conventional fiducial markers, our detection algorithm demonstrated excellent reliability regardless of the display content and background, according to simulation and experimental results. In addition, the detector achieved subpixel accuracy and real-time performance with modern smartphones.     

Moving targets pattern recognition based on the wavelet neural network

Based on pattern recognition theory and neural network technology, moving objects automatic detection and classification method integrating advanced wavelet analysis are discussed in detail. An algorithm of moving targets pattern recognition on the combination of inter-frame difference and wavelet neural network is presented. The experimental results indicate that the designed BP wavelet network using this algorithm can recognize and classify moving targets rapidly and effectively.     

基于肤色检测的快速五官定位算法

根据视频应用的特点，结合人脸的肤色和特征部位几何分布特征，提出了一种应用于视频序列人脸部位的五官定位算法。实验表明，该算法定位速度快，误检率低。     

A CASCADED MODEL OF NEURAL NETWORK FOR PATTERN RECOGNITION

A cascaded model of neural network and its learning algorithm suitable for opticalimplementation are proposed.Computer simulations have shown that this model may successfullybe applied to an error-tolerance pattern recognitions of multiple 3-D targets with arbitrary spatialorientations.     

地面三维目标的探测识别系统研究

针对人员、车辆等地面目标运动时产生的地震动信号,利用地震动传感器采集这些信号并作预处理,再通过模糊识别算法对目标特征进行分类识别,进而构建了一个地面三维目标的探测识别系统.     

Applications of pattern recognition in semiconductor and printed board production

Pattern recognition systems are increasingly replacing the human faculty of visual perception in the production sector. This process is accelerated by the necessity to rationalize production and by the changing demands made upon manufacturing techniques by new technologies.General indications obtained from practical experience are given for the design and application of pattern recognition systems in the production sector. They are brought into focus by examples of applications and approaches, classified according to one-, two- and three-dimensional tasks. Primary consideration is given to examples from microtechniques, especially from semiconductor technology.     

一种表格框线检测和字线分离算法

该文提出了一种基于有向单连通链的表格框线检测算法,能够合理地利用单连通链边沿的全局统计特性和单连通链之间的局部位置关系,精确地提取表格框线,具有抗倾斜,抗断裂,抗字线交叠等优点。在此基础上,提出了一种能够分离交叠字线的表格框线去除算法,并成功应用于实际的表格识别系统中。     

人脸识别中视频回放假冒攻击的实时检测方法

利用合法用户的脸部视频进行回放假冒攻击,是目前人脸认证系统的重要安全威胁。针对此问题,本文提出了一种仅用单个普通摄像头来抵抗人脸视频假冒攻击的方法。不同于以往从人脸区域中获取假冒线索进行活体检测的方法,本文通过人脸输入图像与场景参考图像之间的背景对比,从人脸周围背景区域中寻求视频假冒攻击线索。首先,本文在尺度空间里构建人脸周围区域图像的背景特征点集合;然后,利用背景特征点集合建立识别场地背景和人脸背景的Gabor背景描述子,并用融合相位补差的相似度来进行背景比对。实验表明该方法能有效地识别视频回放假冒攻击。     

识别联机手写体汉字的多级分类方法

本文提出了一种基于笔划的联机手写体汉字多级识别方法，包括拐折码笔划识别方法和笔划位置的模糊匹配方法，拐折码法具有笔划识别率高，对笔划变形的容忍度大，计算简单等特点，笔划位置匹配法不要求笔顺，对书写者的限制比较少，本方法对国标二级汉字的识别率为95％，不要求笔顺，识别速度达到实时要求。     

Antenna selection for MIMO system based on pattern recognition

This paper proposes a novel Multiple-Input Multiple-Output (MIMO) transmission scheme based on Pattern Recognition (PR), which is termed as the PR aided Transmission Antenna Selection MIMO (PR-TAS aided MIMO). As the conventional TAS algorithms need to search all possible legitimate antenna subsets, they may impose some redundant calculations. In order to avoid this problem, we employ some pattern recognition methods to carry out the TAS algorithm in this paper. To be specific, two PR algorithms, namely the K-Nearest Neighbor (KNN) algorithm and the Support Vector Machine (SVM) algorithm, are introduced and redesigned to obtain a TAS with lower complexity but higher efficiency. Moreover, in order to improve the performance of the SVM, we propose a new feature extraction of channel matrix for the TAS. Our simulation results show that the proposed KNN and SVM based PR-TAS algorithms are capable of striking a flexible tradeoff between the complexity and the Bit Error Rate (BER), and the new feature can effectively improve the BER performance compared with the conventional feature extraction method.     

Mandarin tone recognition based on wavelet transform and hidden Markov modeling

This paper presents a method of tone recognition for Mandarin speech by using combination of wavelet transform and hidden Markov modeling techniques. A pitch detector based on singularity detection and multi-resolution analysis of wavelet transform is employed for estimation of pitch periods, and hidden Markov modeling with partition Gaussian mixtures probability density function is used for the tone recognition. The algorithm can provide recognition accuracy of 97.22% and 94.47% for speaker-dependent and speaker-independent tone recognition, respectively.     

多径衰落信道下的一种盲多用户检测方法

多径衰落信道下的盲自适应多用户检测算法的运算复杂度通常都比较大,提出了一种基于MSWF和CMA的盲自适应多用户检测方法,该方法避免了矩阵求逆和信道估计运算,具有相对较小的运算复杂度。通过模拟实验比较了几种算法的误码率性能,结果表明,所提方法具有明显的优势。     

基于模式侧抑制复杂背景下的小目标检测

在复杂背景的图像序列中检测小目标一直是研究重点。提出了一种基于模式侧抑制的复杂背景下小目标检测的方法。将复杂背景下的小目标检测问题看作是在大量相似模式中寻找某个特殊模式的模式识别问题。通过建立基于模式的侧抑制网络模型，在模式空间中对模式进行侧抑制处理，达到突出特殊模式抑制相似模式的目的。同时指出，用该方法对图像进行多级处理可进一步改善处理效果。进行了该方法与去局部均值滤波、基于形态学Top-Hat算子滤波、多级滤波和基于侧抑制理论滤波四种传统方法的比较实验，并将信杂比（SCR）及信杂比增益作为评价算法性能的指标。实验结果表明，提出的方法在提高图像信杂比方面要优于其他几种方法，能有效抑制背景杂波，提高对目标的单帧检测能力。     

训练样本不足时的子空间信号检测方法

为了解决训练样本不足时的子空间信号检测问题,提出了两种有效的降秩检测器.基于主分量分析(PCA)的思想,先把常规自适应子空间检测器中采样协方差矩阵(SCM)的求逆运算用噪声特征子空间矩阵与其共轭转置的乘积代替,构造降秩子空间检测器;为进一步提高算法稳健性,把降秩子空间检测器的求逆运算用Moore-Penrose逆代替.仿真结果表明,所提方法在训练样本充足及不足时,均比现有方法具有更好的检测性能.     

基于ARM7的多批激光威胁信号分选及码型识别

简要介绍了多批激光威胁信号分选及码型识别的原理,利用现场可编程逻辑门阵列FPGA对不同方向的不同时刻到来的3～8位多批脉冲间隔编码信号进行到达时间测量,并将时间数据通过32位总线送给32位嵌入式处理器ARM7进行信号分选和码型识别。给出了FPGA内部信号流程以及ARM7进行信号分选及码型识别的算法,并通过测试证明了该算法的有效性以及分选速度快、准确率高的特点。在实际应用中,利用此方法,提高了某型装备信号分选和码型识别的能力。     

图像识别技术在铁路设备故障检测中的应用

为了提高铁路行车安全性,对铁路设备进行有效地故障检测是不可或缺的环节。文中提出一种基于图像识别技术的设备故障检测方法,该方法解决了机车在运行期间各设备状态的动态检测问题,主要以动态图像为研究对象并进行实时处理。最后通过实验验证了文中研究工作具有快速、准确度高等特点。     

基于边缘检测的车牌识别算法的实现

针对传统车牌识别的不足,本文提出了基于边缘检测的车牌识别的算法.该算法首先对摄像头获取的车牌图像预处理,去除图像无用信息,然后运用Robert算子检测车牌边缘,并对车牌区域进行图像较正,用高斯滤波法去除噪声并且提取车牌信息特征,接着对车牌区域水平和竖直方向运用触点定位法分割字符,对车牌分割后与相应字符模版匹配,利用预测模型预测识别结果,最后识别出车牌字符.