GeodesiActiveContour

用sift算子对两幅图像进行特征点的自动搜索。(Sift operator with the image feature point english)

本程序用于对工件图像的预处理，边缘提取等。将改进遗传算法和Hausdorff距离结合用于工件识别。采用canny边缘为匹配特征，将修正的Hausdorff距离作为相似性度量准则，并应用遗传算法进行最佳匹配的快速搜索，成功实现了目标物体的匹配识别(This procedure used for the workpiece image preprocessing, edge extraction and so on. Will improve the genetic algorithm and Hausdorff distance combination for workpiece identification. Using canny edge for matching characteristics, will be amended Hausdorff distance as similarity measurement criteria and the application of genetic algorithm is the best match of the Quick Search, the successful achievement of the target object matching identification)

利用直方图双峰法选取适当阈值对图像进行二值化处理。此法只适用于直方图为双峰状图像。(Using the Shuangfeng method to the appropriate threshold histogram of image processing two values. This method is only applicable to the histogram of image of Shuangfeng.)

图像修复的改进算法，RPCA算法程序代码，实现图像的去噪和复原(Improved algorithm of image restoration, RPCA algorithm program code, to achieve image denoising and restoration)

针对杂波环境下的多个机动目标跟踪问题, 本文将多模型概率假设密度 (Multiple-model probability hypothesis density, MM-PHD) 滤波器和平滑算法相结合, 提出了 MM-PHD 前向 – 后向平滑器. 为了避免引入复杂的随机有限集 (Random finite set, RFS) 理论, 本文根据 PHD 的物理空间 (Physical space) 描述法推导得到了 MM-PHD 平滑器的后向更 新公式. 由于 MM-PHD 前向–后向平滑器的递推公式中包含有多个积分(By integrating the multiple-model probability hypothesis density (MM-PHD) filter with the smoothing al- gorithms, an MM-PHD forward-backward smoother is proposed in this paper for tracking multiple maneuvering targets in clutter. To avoid use of complex random finite set (RFS) theory, the backward updated equation of the MM-PHD smoother can be derived according to the physical-space explanation of the PHD)

图像处理中的数字识别代码，包括数字训练集合和训练分类算法，可以实际应用。(digital recognition)

用kfcm算法实现数据的聚类和分类效果。(Kfcm algorithm is used to achieve data clustering and classification results.)

大量图片的处理代码,特别是图片的批量处理，非常有利于在处理图片时使用(A large number of image processing code, especially images of batch processing, image processing is very conducive to the use of)

用harris算法对图像进行角点检测,输出为这些点的坐标的矩阵(Harris algorithm using corner detection image, the output for these points, the coordinates of the matrix)

某个平面内的一系列点的密度分布，通过求出x和y方向的点的概率，最后用矩形框画出密度大的区域。4000个数据，详解，效果不错，直接能运行。(The density distribution of a series of points in the plane, determined by the probability of the point x and y directions, the final draw-density region with a large rectangular box. 4000 data, explain, good results can be directly run.)