duiying

shi-tomasi方法角点提取方法。该方法测量结构张量的最小特征值。这代表了Harris和诺贝尔探测器试图近似的理想。哈里斯希望在计算特征时避免计算平方根的计算成本。(Shi-Tomasi corner detector method.The method measure returns the minimum eigenvalue of the structure tensor. This represents the ideal that the Harris and Noble detectors attempt to approximate. Back in 1988 Harris wanted to avoid the computational cost of taking a square root when computing features. This is no longer relevant today!)

说明：  用FCM算法实现图像分割(图像源可以是灰度、索引和RGB图像)(FCM image segmentation algorithm (image source can be gray, indexes and RGB images))

里面有注释，还有sift和surf的比较(There are notes, there are more sift and surf the)

本算法应用hough变换对车道进行直线检测，对于系统拍摄到的路面进行车道检测。(Application of this algorithm hough transform for line detection of the lane, shooting for the system to carry out road-lane detection.)

完成声音信号的分帧，加窗，PLCC特征提取等功能(Complete voice framing, windowing,PLCC detection and other functions)

模式识别相关技术，EM算法简介，EM算法是关于半监督学习的一种技术(Pattern recognition technology, EM algorithm About, EM algorithm is on a semi-supervised learning techniques)

根据GetVersionEx获取版本ID获取系统名称(According GetVersionEx version ID for the system to obtain the name of)

改进的otsu算法，计算局部otsu的值确定局部小区域。对于光照不均匀图像处理有比较好的适应( Improved otsu algorithm to calculate the value of the local otsu determine the local small area. For uneven illumination image processing has a relatively good adaptation)

基于边缘特征的图像配准算法源码 基于边缘特征的图像配准算法是将不同时间、不同的传感器（成像设备）或不同条件下（天候、照度、摄像位置和角度等）获取的同一场景的两幅或多幅图像根据其边缘特征进行匹配、叠加的处理，最终生成一幅全景图像的方法。该方法具有抗噪性强，匹配速度快，误匹配率低，适用于多种类型的图像等优点，主要可以运用于以下领域： （1）军事研究领域，如飞行器辅助导航系绞、武器投射系统的末制导以及寻地等应用研究； （2）医学图像分析，如数字剪影血管造影DSA血管造影术、肿瘤检测、白内障检测、CT、MRI、 PET、 SPECT图像结构信息融合； （3）模式识别，如特征识别、波形分析、签名证实、目标物运动跟踪、序列图像分析等； （4）计算机视觉，可用于目标定位、自动质量控制等； （5）遥感数据分析，多电磁波段图像信息融合，如多谱段的等场景分类、定位和识别定义好的或已知特征的场景、自然资源监控、核生长监控、市区增长检测等。 本算法实现使用VC++6.0为开发环境，目前只支持灰度图像，感兴趣的朋友可以进一步扩展。(Image registration is a fundamental problem in image processing, which is a process to match two or more images of the same scene taken at different times, from different viewpoints, or by different sensors. Image registration is an important technique for a great variety of applications such as medical image analysis, computer vision, remote image data analysis, image information fusion, and the recovery of the 3–D characteristics of a scene.)

多光谱图像出理，离散傅立叶变换，低通滤波，TM条带影像去除(multispectral image integration of remote sensing)