CO_SUT

c#下实现图像颜色k均值聚类 将像素点颜色分类并合并(c# implementation of color image k-means clustering to classification of color pixels and merge)

本文提出了一个关于图像抠图的方法，它的抠图效果不错，而且作者的主页上提供了MATLAB的源码，可以看一下。(This paper presents a method on the image matting, matting it well, and the author' s home page provides a MATLAB source code, you can see it.)

opencv,图像处理，关于物体粘连问题的检测，基于凹性分析的分割方法(opencv, image processing, object sticking problem on detection, segmentation method based on analysis of the recess)

用于通过三维激光点云数据生成二维的地理参考特征图像，此处以高程作为特征(Used by 3 d laser point cloud data to generate two-dimensional geographical characteristics of reference image, the elevation as features)

说明：  用MATLAB实现不规则图像的面积测量，采用像素灰度值的占比进行实现(Area Measurement of Irregular Images Using MATLAB)

用matlab对点云数据进行曲面分析，对三维点云配准算法有很大的改进作用。(Using matlab for point cloud data for surface analysis, the three-dimensional point cloud registration algorithm has greatly improved effect.)

说明：  基于HARRIS特征点的数字水印的嵌入算法，以及数字水印的检测算法(Watermark embedding and Detection in image based on Harris features points)

SURF算法作为一种新近出现的特征提取方法，在重复度、独特性、鲁棒性3个方面，均超越或接近以往提出的同类方法，并在计算效率上具有明显的优势。本代码采用SURF算法检测图像并进行坐标变换与图像拼接。 采用SURF算法对图像进行检测，其主要是用Hessian矩阵对图像进行检测，对图像的特征提取之后找到图像的特征点。之后采用最近临快速匹配（NN）、随机抽样一致性（RANSAC）算法和最小二乘法参数优化（LM）对特征点进行提纯匹配。最后在两幅图像中进行坐标变换，达到统一坐标系和图像拼接的效果。 (SURF（Speeded Up Robust Features） as a method of feature extraction which newly appeared is over or nearly previous method on duplication, uniqueness, and robustness and have a clear advantage on computational efficiency. This code uses the SURF and coordinate transformation algorithm to detect image and image matching. This code uses the SURF algorithm of image detection, the main is to use the Hessian matrix of image for testing, to find the image after image feature extraction of feature points. After we used Nearest Neighbor (NN), Random Sample Consensus (RANSAC) algorithm and least square parameter optimization for purification of matching feature points. Coordinate transformation in the last two images, to coordinate system to achieve the same image stitching. )

分为行人检测，特征提取，行人跟踪三步，其中最主要的代码也是这个代码的中心是行人跟踪这一部分，我采用的是kalman滤波器进行行人下一帧位置的预测，可以很好的提高行人跟踪的鲁棒性，跟踪结果比较准确。(Into pedestrian detection, feature extraction, pedestrian tracking steps, which is the center of the main code of the code is pedestrian tracking this section, I kalman filter is used to predict the position of the next frame pedestrians, can be a good improvement pedestrian tracking robustness, tracking results more accurate.)

说明：  用OSTU和KSW实现多阈值图像分割，matlab代码(Image Segmentation Using OSTU and KSW)