拟合

一种基于otsu的二维灰度图像分割算法，包括注释和源代码，适合初学者使用。(A two-dimensional gray image segmentation algorithm based on Otsu, including annotation and source code, which is suitable for beginners.)

利用matlab实现Patchwork算法，包括各种处理攻击(Using matlab Patchwork algorithm, including the attack of various treatment)

给予分水岭的图像分割，包括源代码、测试图、实验报告(Given watershed image segmentation, including source code, test plans, test reports)

利用数字图像处理软件halocn来进行缺陷检测，附带有之前做工程项目的原图源代码，还有ppt和实验指导书(Halocn using digital image processing software for defect detection, comes with artwork done before the project source code, as well as ppt and experimental instructions)

matlab下图文并茂的分析了fft算法，分析了如何从频谱如何看频率，相位，幅值(Here to enter through the abundant of matlab analyzed fft, and analyzed from the frequency spectrum how to see that phase, should be translated text)

读取使用YUV格式视频的一系列函数，包括LoadYUV，saveYUV，YUV与RGB直间的相互转换等(Read YUV format video series of functions, including LoadYUV, saveYUV straight between YUV and RGB conversion)

说明：  该课题为基于MATLAB的汽车出入库识别系统，带有丰富的人机交互GUI界面。目前毕业设计选题中，传统的中规中矩的车牌识别不易得到高分，必须要在此基础上有所创新方得可以避开其他雷同课题，不会轻易被导师被否决而导致毕设不过。因此建议在车牌识别基础上加入多种方法的对比，看看哪种方法的精度高。虽然目前有很多方法的车牌识别，但是都是在各自的测试库里面测试的，比如测试的车牌图像不同，字符库不同，导致无法做对比。整个设计在一个GUI界面上完成。(This project is based on MATLAB vehicle in and out of the warehouse identification system, with rich human-computer interaction GUI interface. At present, in the topic selection of graduation project, the traditional regular license plate recognition is not easy to get high scores, so it is necessary to innovate on this basis to avoid other similar topics, and it will not be rejected easily by the tutor, leading to the failure of graduation project. Therefore, it is suggested to add a variety of methods on the basis of license plate recognition to see which method has high accuracy. Although there are many methods of license plate recognition, they are tested in their own test library, for example, the test license plate image is different, the character library is different, so it can not be compared. The whole design is completed on a GUI interface.)

有关三维模型的泊松算法的诸多应用的实现，包括泊松重建和泊松纹理混合算法，由原作者开发，非常可靠(C++ implementation for algorithms including poisson mesh and poisson texture stitching, it is shared by author with wide utilization)

灰度图像的属性计算：利用bwlabel和regionprops函数对度量二值图像中目标对象的属性。(Attribute gray image: Using bwlabel and regionprops function measure binary image of the target object attributes.)

IMM算法，用于机动目标的精确跟踪和定位，该模型集考虑了三种典型子模型:CV,CT,CA. (interacting multiple model (IMM) code for target tracking )