ellipserecognise

该函数用于简单背景下运动目标检测和轮廓提取，虽为简易实现，但效果不错，可根据个人需要添加代码(This function for a simple moving object detection and contour extraction, although it is easy to achieve, but good results can be based on individual need to add code)

传统的几种图像增强与去噪方法，包括直方图处理，灰度变换，滤波去噪等几类。细分为直方图均衡化，直方图规定化，灰度线性变换，中值滤波，维纳滤波，同态滤波(The traditional methods of image enhancement and denoising include histogram processing, grayscale transformation, filtering and denoising. Subdivided into histogram equalization, histogram specification, gray level linear transformation, median filtering, Wiener filtering, homomorphic filtering)

wincc脚本数据手册，最全的C脚本，介绍详细，官方资料(wincc cript data manual, the most complete C script)

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.)

摄影测量点云，三维激光点云进行点云特征图像提取进行格网化代码(Photogrammetric point cloud, 3D laser point cloud, point cloud feature image extraction for grid code)

说明：  一种基于粒子滤波的测向定位跟踪算法，一种基于粒子滤波的测向定位跟踪算法。(A particle filter based on the finding and location tracking algorithm, a particle filter based on the finding and location tracking algorithm.)

利用互信息进行特征抽取的方法实现，能找到最具代表的特征，有效的实现了计算量的减少和可用来维数缩减(The use of mutual information feature extraction method of implementation, to find the most representative characteristics of an effective implementation of the computation of the reduction and can be used to reduce the dimension)

图割（GC)和主动轮廓模型（ACM)相结合的一种图像分割方法，既可以进行局部图像的分割，也可进行全局图像的分割，简单实用。(A combination of graph cuts (GC) and the active contour model (ACM) image segmentation method, either local image segmentation, global image segmentation, simple and practical.)

用于人脸识别边缘检测，实现5个尺度、8个方向的检测。(Edge detection for face recognition)

Gray Level Edge Thinning Method Abstract. An effective edge thinning algorithm is important in image segmentation and object identification since it increases the possibility of success in detecting objects in the image and saves the processing time in the further steps such as labeling and image transformation. We investigate some gray level edge thinning method that is based on the gradient magnitude within 3x3 local neighborhood. The new method has been tested with various types of images the real world. Experimental results show that this method produces more accurate images than those of the popular non-maximum suppression methods do.