gaotonglvbo

基于卡尔曼滤波器的监控系统的设计，实现了对运动目标进行识别，并对其运动轨迹进行预测的功能；当二值化图像超过一定阈值时，判断为有外人入侵，实现报警功能。(Kalman filter based on the design of monitoring system to achieve the recognition of moving objects, and its motion trajectory prediction function when the binary image exceeds a certain threshold, to determine the invasion of outsiders, to achieve alarm function.)

利用MATLAB实现NSCT非下采样轮廓波变换(Realization of Nonsubsampled Contour Transform by Using MATLAB.)

MODIS图像批量镶嵌拼接方法（IDL/ENVI）(modis mosaic)

C++ based JPEG on grayscale image DCT -> Quantization -> ZigZag -> DPCM, Runlength,-> Entropy Coding

基于Canny算子检测图像边缘，其中含有非极大值抑制功能。(Based on Canny operator edge detection image, which contains a non-maxima suppression.)

首先将RGB转换到HSV，再根据阈值进行HSV图像的分割(First convert RGB to HSV, then HSV image segmentation based on threshold)

利用SFS算法实现3D图像重建，附带有图片实现(3D Image Reconstruction Using SFS Algorithms)

ViBE背景建模算法，从 PC上移植改编，可在嵌入式上运行，效率较高(ViBE background modeling algorithm, coded PC to imbeded. )

质心点求取，目标进行形跟踪，跟跟踪物体。希望高手指点(Centroid strike, shaped track)

SIFT，即尺度不变特征变换（Scale-invariant feature transform，SIFT），是用于图像处理领域的一种描述。这种描述具有尺度不变性，可在图像中检测出关键点，是一种局部特征描述子。[1] 该方法于1999年由David Lowe[2] 首先发表于计算机视觉国际会议（International Conference on Computer Vision，ICCV），2004年再次经David Lowe整理完善后发表于International journal of computer vision（IJCV）。截止2014年8月，该论文单篇被引次数达25000余次。(SIFT, namely Scale Invariant Feature Transform (Scale-invariant feature transform, SIFT), it is a description for image processing. This description has scale invariance, can detect critical point in the image, it is a local feature descriptor. [1] The method in 1999 by David Lowe [2] First published in the International Conference on Computer Vision (International Conference on Computer Vision, ICCV), 2004 was again perfect finishing after David Lowe published in the International journal of computer vision (IJCV) . As of August 2014, the paper cited the number of times a single article of more than 25,000 times.)