quyunengliangquda

用python实现图像的LBP特征提取，参数可以自己修改。(Get a LBP image original binary image with python.)

基于直接最小二乘法的椭圆拟合程序，比较实用，适用于图像处理，椭圆拟合方面研究的初学者(Direct least square method based on ellipse fitting procedure more practical for image processing, aspects of ellipse fitting for beginners)

ITK的脑室图像分割,可以对脑部的图像用itk进行分割，用VTK来进行显示。(the segration of brain of ITK )

用于分割2D、3D图像的可交互graph cut程序，纯matlab实现，不含C++(An interactive graph cut program segmenting 3D images)

一种区域生长算法，用于图像分割。自动选择种子点。(A Region Growth Algorithm for Image Segmentation)

Image retrieval lecture

说明：  图像去噪，梯度倒数加权滤波代码噪matlab中实现(Image denoising, countdown weighted gradient noise filtering matlab code to achieve)

针对粒子概率假设密度(PH D)滤波算法在虚警、漏检情况下，b标状态估计不稳定和b标可观测性车弱的问题，提出了一种基于序贯融合的粒子PH D滤波方法，利用雷达和红外传感器多目标进行融合跟踪杏基本思想是先对红外传感器进行粒子PH D滤波，丙将红外传感器滤波结果作为雷达的预测值，然后利用P达观测的数据进行更新，这样通过雷达和红外传感器交替上作保证目标状态的可观测性，从滤波器输出结身即可得到目标的状态信息仿真结果表明，在虚警、漏检和密集目标环境下，该方法是有效的和稳健的(The problem of target state estimation instability and observability weakerin the presence offalse alarms and missed detection was deal with. On the basis of sequential fusion, a particleprobabil- ity hypothesis density(PHD) filter for multrsensor multrtarget tracking was proposed. Observed da to collected from the infrared sensor was estimated with the particle PHD filter. Then the results from the filter were set as the radar predicted value by the radar observations. The multrtarget state can be updated to guarantee observing the target state. In this way, the global state is updated at the fusion center. Simulation results show that the proposed algorithm is effective and robust under the false warning, omission and concentrated target environment. )

说明：  基于hessian矩阵的眼底图像血管增强滤波(Vessel Enhanced Filtering of Eyeground Images Based on Hessian Matrix)

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.)