基于区域的主动轮廓模型算法论文RegionBasedSnake

画图源程序-图像数据显示，可以对数据进行时间轴的曲线显示，也可以是空间轴的多维显示 (Paint source- the image data, the data can be curve shows the time axis, it can be multi-dimensional display space axis)

opencv读取一个视频并设置其播放帧率播放速度(use opencv to read a video and change the rate)

在文档下打开一个位图文件，重新绘制，放大并使其二值化显示，()

灰度图像图像锐化处理，拉普拉斯变换，梯度等(Grayscale image sharpening, Laplace transforms, gradients, etc.)

数学形态学及相关算法的C语言实现实例 源代码调用OpenCV的cxcore和highgui两个库，应用C语言编写，实现对染色体图像中染色体数目的统计。代码中的核心算法为数学形态学的重要算法——开运算、闭运算（腐蚀和膨胀）。包含腐蚀处理、膨胀处理、自适应中值滤波、微分直方图法确定二值化阈值、种子填充算法等图像处理算法的C语言实现，值得参考。(Mathematical Morphology and related algorithms realize the C language source code examples of cxcore call OpenCV and highgui two libraries, the application of C language to realize pairs of chromosomes in the chromosome number of image statistics. The core algorithm code for an important mathematical morphology algorithms- open operation, closing operation (corrosion and expansion). Contains corrosion treatment, expansion of treatment, adaptive median filter, histogram method to determine differential binarization threshold, the seed fill algorithm, such as image processing algorithms realize the C language, it is also useful.)

图像球面化，对于输入的图片进行球面变换达到图形变形的效果(Spherical image of, for input images to spherical transformation to achieve the effect of graph distortion)

EDLines是一种快速直线检测算子，2012年在ICCV上提出，也是目前处理直线检测最快的算法之一，该算法包含三个步骤：（1）边缘提取：利用Edge Drawing (ED)算法[28,29]从灰度图像中提取边缘片段；（2）线段检测：利用最小二乘法提取直线段；（3）线段确认：遵循Helmholtz定律，从已提取的直线段中摒弃虚假线段。EDLines算法的优越性得益于Edge Drawing (ED)算法能够从灰度图像中准确、快速、稳定地提取出光滑、完整的边缘片段。Edge Drawing (ED)算法包含以下步骤： （1）采用size=5*5,σ=1的高斯核对灰度图像进行平滑滤波，去除噪声； （2）采用一种常用的梯度算子，如Prewitt、Sobel或Scharr等计算平滑后图像中每个像素点的梯度幅度和梯度方向； （3）将梯度图中邻域内幅度最大的像素点标记为锚点，这些锚点成为图像边缘点(edge elements)的概率很大； （4）将相邻的锚点连接成边缘线。从一个锚点起始，ED利用相邻像素的梯度幅度和方向在梯度为最大值的锚点之间游走。 (Edge Drawing (ED) is our recently-proposed, novel, fast edge detection algorithm. What makes ED stand out the existing edge detectors, e.g., Canny, is the following: While the other edge detectors give out a binary edge image as output, where the etected edge pixels are usually independent, discontinuous entities ED produces a set of edge segments, which are clean, contiguous, i.e., connected, chains of edge pixels. Thus, while the output of the other edge detectors requires urther processing to generate potential object boundaries, which may not even be possible or result in inaccuracies ED not only produces perfectly connected object boundaries by default, but it also achieves this in blazing speed compared to other edge detector.)

基于opencv的Kinect深度图像的去噪，滤波(Opencv based Kinect depth image denoising, filtering)

desing and develop a cube rotation

多径条件下基于加权空间平滑的阵元幅相误差校正(Multipath based on weighted spatial smoothing array element amplitude and phase error correction)