过特定人语音情感数据库的建立；语音情感特征提取；语音情感分类器的设计，完成了一个特定人语音情感识别的初步系统。对于单个特定人，可以识别平静、悲伤、愤怒、惊讶、高兴5种情感，除愤怒和高兴之间混淆程度相对较大之外，各类之间区分特性良好，平均分类正确率为93.7 。对于三个特定人组成的特定人群，可以识别平静、愤怒、悲伤3种情感，各类之间区分特性良好，平均分类正确率为94.4 。其中分类器采用混合高斯分布模型。(The system of speech emotion recognition)
利用Visual C++实现AVI文件的图像截取 实现对图像数据的读取显示 实现视频图像处理技术 编程中如何操作数据库中的图像字段 实现数字图像增强处理(Use Visual C++ AVI file image interception To read the image data display Video image processing technology Programming how to operate the database image field Digital image enhancement)
1.模式匹配：子串在主串中的定位，也叫字符串匹配。模式匹配成功是指在主串S中能够找到模式串T，否则，称模式串T在主串S中不存在。 2.模式匹配的应用在非常广泛。例如，在文本编辑程序中，我们经常要查找某一特定单词在文本中出现的位置。 3.模式匹配算法的研究能极大地提高文本编辑程序的响应性能。 (1 pattern matching: substring positioned in the main string, also called string matching. Pattern matching refers success can be found in the main string S pattern string T, otherwise known as pattern string T does not exist in the main string S. 2 pattern matching in a very wide range. For example, in a text-editing program, we often have to find the location of a particular word appears in the text. 3 study of pattern matching algorithms can greatly improve the response performance of text editing program.)
可以将256色度级的图像转化为灰度图象，挺值得新手学习一下的，希望大家能喜欢(256 chroma level images can be converted to grayscale images, very worth novice to learn about, and I hope you like)
基于非局部图像去噪模型的遥感图像融合的变分方法。该变分方法采用梯度下降法。(Variational method of remote sensing images nonlocal image denoising model fusion. The variational method using gradient descent.)
光斑中心提取算法，在VS2010下，用opencv2.3.1编写的控制台程序，主要功能是利用hession矩阵和高斯滤波进行光斑中心点提取，里面附测试图片，提取精度为亚像素级别。(Spot center extraction algorithm, in VS2010, written by opencv2.3.1 console program, the main function is to use hession matrices and Gaussian filter for extracting the center spot, which is attached test images, the extraction accuracy of sub-pixel level.)
混合高斯(Mixture of Gaussian, MOG) 背景建模算法和Codebook 背景建模算法被广泛应用于监控视频的运动目标检测问题, 但混合高斯的球体模型通常假设RGB 三个分量是独立的, Codebook 的圆柱体模型假设背景像素值在圆柱体内均匀分布且背景亮度值变化方向指向坐标原点, 这些假设使得模型对背景的描述能力下降. 本文提出了一种椭球体背景模型, 该模型克服了混合高斯球体模型和Codebook 圆柱体模型假设的局限性, 同时利用主成分分析(Principal components analysis, PCA) 方法来刻画椭球体背景模型, 提出了一种基于主成分分析的Codebook 背景建模算法. 实验表明, 本文算法不仅能够更准确地描述背景像素值在RGB 空间中的分布特征, 而且具有良好的鲁棒性.(The background modeling algorithm of mixture of Gaussian (MOG) and codebook is widely used in moving object detection of surveillance video. However, the ball model of MOG usually assumes that the three components of RGB are independent, while the cylinder model of codebook assumes that the value of background pixel is distributed uniformly within the cylinder and the changing direction of brightness points to the origin of the coordinate system. These assumptions reduce the descriptive capability for background modeling. Therefore, the paper proposes an ellipsoid- based background model, which overcomes the MOG and codebook0s limitations. By using principal component analysis to depict the ellipsoid background model, a novel PCA-based codebook background modeling algorithm is proposed. Experiments show that this algorithm can not only give more accurate description of the distribution of background pixels but also have a better robustness.)
在VC6.0环境下，借助openCV函数库，对视频中的人脸进行检测，并实时跟踪，然后用Haar特征的分类器定位人脸，并检测瞳孔存在与否，提取关于眼睛的疲劳信息(In VC6.0 environment, with the aid of openCV function library, to detect human faces in video, and real-time tracking, positioning and use characteristics of Haar classifier faces, and examine the pupil existence, to extract the information about the fatigue of the eye)
图形裁剪，实现对画的线，多边形，交点进行剪裁，实现图形的规范化(Graphic cutting, to achieve the painting line, polygon, tailoring intersection, graphics standardization)
SURF 图像特征点快速提取法还有描述，可用于迅速匹配两张图片中的特征点(SURF image feature points extraction method also described fast, can be used to quickly match the image feature points in the two)
图像处理实习（针对遥感影像），包含许多经典的图像处理功能，比如多种植被指数计算、小波变换、镶嵌、图像分类等(Image processing internship (for remote sensing images), contains many classic image processing functions, such as a variety of vegetation indices, wavelet transform, mosaic, image classification, etc.)
本书系统地介绍了图像处理与识别的基本原理、典型方法和实用技术。全书共分12章，第1章～第6章是图像处理与识别的基础内容，包括图像科学综述、MATLAB语言图像编程、图像增强、图像分割、图像特征提取和图像识别；第7章～第10章是图像处理与识别的工程实例，涵盖了医学图像处理、文字识别和自导引小车路径识别等应用实例，并结合理论算法，提供了大量MATLAB代码程序，以帮助读者掌握如何使用MATLAB语言快速进行算法的仿真、调试和估计等方法。第11章～第12章，是两个综合性较强的实例，分别是Visual C++实现的基于神经网络的文字识别系统和车牌定位系统。 本书附带的光盘给出了各个章节列举的实例的源代码，同时赠送了28个常用数字图像处理算法的Visual C++代码实现。 本书讲解深入浅出，实例程序丰富，注重理论与实践相结合。本书可作为计算机应用、自动化、图像处理与模式识别、机电一体化专业的高年级本科生或研究生的参考书，也可供从事图像处理与识别的研究人员和工程技术人员阅读参考。(This book introduces the basic principles of image processing and recognition of the typical methods and practical skills . The book is divided into 12 chapters , Chapter 1- Chapter 6 is the basis of the content of image processing and recognition , including images scientific overview , MATLAB programming language images, image enhancement, image segmentation, image feature extraction and image recognition Chapter 7- Section Chapter 10 is a project example image processing and recognition , covering the medical image processing, character recognition and self- guided trolley path recognition example , the combination of theory and algorithms, for a lot of MATLAB code procedures to help readers learn how to use MATLAB language fast simulation , debugging and estimation methods algorithm. Chapter 11- Chapter 12 , are two examples of highly integrated , namely Visual C++ implementation based on neural network character recognition system and a license plate positioning system. The book)
Downsample image console program using opencv.
使用OpenCV实现特征点的查找以及两幅图像中的特征点匹配(Use the function findHomography to find the transform between matched keypoints. Use the function perspectiveTransform to map the points)
2014年海康威视校招笔试题，对于想要从事图像处理工作的同学十分有用，图像处理算法类试题，考的是C语言和C++.图像算法类题目不常见。(2014 Hikivision exam)
OpenCV_基于混合高斯模型GMM的运动目标检测。内附监测监控视频，方便测试使用。(OpenCV_ GMM Gaussian mixture model based moving target detection. Included monitoring surveillance video, easy testing.)
OpenCV_基于混合高斯模型GMM的运动目标检测。内附监测监控视频，方便测试使用。(OpenCV_ GMM Gaussian mixture model based moving target detection. Included monitoring surveillance video, easy testing.)
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