Accuracy-evaluation

基于小波变换的图像融合源程序，通过调试，能直接使用。(Image fusion based on wavelet transform source code through the debugger can be used directly.)

avi视频提取出书帧图像，然后对图像进行处理，经过处理后的图像帧再写成另一段的avi视频。(avi video video frame extracted, processed image frame, and then the images will be referred to the district into another frame of video avi.)

用于信号特征提取、信号消噪，MinkowskiMethod算法 ,未来线路预测,分析误差。( For feature extraction, signal de-noising, MinkowskiMethod algorithm, Future line prediction, error analysis.)

此ransac为图像匹配的一个重要环节，可以实现更复杂的图像匹配(The RANSAC is an important part of image matching, the image can be more complex matching)

利用随机霍夫变换进行圆的检测，matlab编写(Randomized Hough transform for circle detection, Matlab prepared)

利用霍夫线检测实现车道线的自动检测并判断是否偏离(Using Hof line detection to achieve automatic detection of lane line and determine whether or not to deviate the)

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)

图像处理缩放，大小随意改变，平滑处理，基于vb6.0设计(Zoom image processing, size change, smooth deal, based on the design VB6.0)

操作简单，实现双目视觉下的三维重建，输入双目下两张图片，生成渲染后的重建结果。(Simple, to achieve a three-dimensional reconstruction under binocular vision, binocular enter under two pictures, generated reconstructions rendered.)

说明：  针对弱小目标信号提出的RXD异常检测算法，实现对目标的检测(A RXD anomaly detection algorithm for dim and small target signals is proposed to realize target detection.)