shapecontext6

说明：  KFCM聚类算法进行图像分割，分割效果好(KFCM clustering algorithm for image segmentation, segmentation effect is good)

OPENCV图像处理模板，有界面编程的，以后运用opencv直接在里面填写代码就可以了(OPENCV image processing template, with interface programming, and after using opencv code directly on the inside can be a complete)

自适应中值滤波，对图像的椒盐噪声有很好的滤除效果，非常不错的程序(Adaptive median filter, the image of the salt and pepper noise filtering effect of a very good, very good procedures)

本代码主要是基于HSV的阴影检测及消除，分别提取前景及背景图像，进行色彩空间转换。HSV空间类似人类感觉色彩的方式，可以更加准确地识别阴影，并保持在计算上简单。(This code is mainly based on the HSV shadow detection and elimination, extract the foreground and the background image, respectively, for color space conversion. HSV space is similar to the ways the human feel color, can more accurately identify the shadow, and keep it simple in calculation. )

提出了一种针对复杂环境下的过人脸检测方法，首先在CbCgCr空间利用直接最小二乘法构建了对光照和复杂背景鲁棒性更好肤色聚类模型，实现了准确的肤色检测；然后针对人脸中姿态和表情变化，提出了基于Adaboost的多姿态人脸检测，精确的实现了人脸检测定位。(Extraordinary face detection method for complex environments, the first space CbCgCr ​ ​ direct least squares method to build a better robustness to light and complex background color clustering model to achieve accurate color detection forface, posture and facial expression changes, proposed the multi-pose face detection based on Adaboost, accurate face detection and location. )

两船协同导航，利用EKF滤波，主要用于主从式的协同导航，滤波参数要根据实际需要合理调节(Collaborative navigation of both vessels, the use of the EKF filter, mainly used for the master-slave collaboration navigation filter parameters according to the actual needs of a reasonable adjustment)

摄影测量中影像匹配的程序，选择左右影像，可直接显示匹配结果。程序用C#编写(Photogrammetry image matching procedures, C# Prepared)

说明：  对限制对比度自适应直方图均衡化算法adapthisteq进行了解释。可用于图像增强(Contrast to the limited adaptive histogram equalization algorithm adapthisteq is explained. Can be used for image enhancement)

本实例用到了第三方组件ICSharpCode.SharpZipLib.dll、itextsharp.dll。

基于梯度相似度的图像质量评价方法，发表在2012年TIP国际期刊上(A. Liu, W. Lin, M. Narwaria, “Image Quality Assessment Based on Gradient Similarity,” IEEE Transactions on Image Processing, vol. 21(4), pp. 1500-1512, 2012.)