zhongxin

利用matlab和ceemd进行编程求解简单的信息熵，根据求解的imf分量判断信号的情况(Using MATLAB and ceemd programming to solve simple information entropy, according to the IMF component to determine the situation of the signal)

这是一个基于超像素算法的分割小软件，可以用于图像的分割，但是没有语义。使用者如果用于商用，要联系软件中的作者(This is a small software based on super-pixel algorithm, which can be used for image segmentation, but without semantics. Users for commercial use should contact the authors in the software.)

this Class used to re-sampling image and convert at as you wont and as u need to use it in your program

Image to be embedded into an image

说明：  python实现人脸识别，通过pca进行降维然后使用SVM算法进行分类(Python realizes face recognition, dimensionality reduction through pca and classification by SVM algorithm)

JPEG2000matlab实现 最新的图像压缩标准(JPEG2000matlab achieve the latest image compression standard)

对静态图像应用canny算法提取边缘特征(The edge feature is extracted by canny algorithm of static image)

利用matlab 对高速公路的裂缝进行检测，用到了数字图像处理的基本算法(The use of matlab on the highway crack detection, using the basic digital image processing algorithms)

一个生成NURBS曲面的程序，是在Visual下运行的(A NURBS surface generation program is run under Visual)

说明：  虚拟内窥镜关键技术研究 虚拟内窥镜技术（Virtual Endoscopy）是虚拟现实技术在现代医学中 的应用。它利用医学影像作为原始数据，融合图像处理、计算机图形学、科 学计算可视化、虚拟现实技术，模拟传统光学内窥镜的一种技术。它克服了 传统光学内窥镜需把内窥镜体插入人体内的缺点，是一种完全无接触式的检 查方法。虚拟内窥镜的研究旨在为医生提供诊断依据，还可应用于辅助诊断、 手术规划、实现手术的精确定位和医务人员的培训等。(Research on key technologies of virtual endoscopy virtual endoscopy (Virtual Endoscopy) is a virtual reality technology in modern medicine. It has made use of medical imaging as an original data, the integration of image processing, computer graphics, scientific visualization, virtual reality technology to simulate a conventional optical endoscope technology. It overcomes the traditional optical endoscope to be inserted into the endoscope body of the shortcomings of the human body is a no-contact inspection method. Virtual Endoscopy of the study was to provide diagnosis for doctors, but also applies to diagnosis, surgical planning, to achieve precise positioning of surgical and medical personnel training.)