image-segmentation

使用VC++ 6.0 和 OpenCv实现粒子滤波目标跟踪算法，主要功能在MFC对话框内实现。(particle filter object tracking)

使用CGAL库对人体三维网格分割并且把分割后的网格展开到一个平面上(using cgal to segment a mesh an expend )

这是香港大学沙威博士写的压缩感知引论及相应的OMP算法。(This is written by the University of Hong Kong, Dr Savit compressed sensing cited dealt with the OMP algorithm.)

自写M函数，做灰度图像的灰度级数及灰度范围的自定义设置。例如：将[0 255]的uint8图像变换成8级灰度的灰度范围为[0 7]图像或者[11.5 25.8]图像。 输出图像为double类，用户可将图像归一化后自行转换为所需类型。(This is a M function written by self, it can be used to rebuild a image with a given number of gray-level and a given gray-scale. Output image is double class.)

对低质量图像分割和计数，以大米照片为例。(Of low-quality image segmentation and counting to rice as an example photo.)

目标跟踪程序,使用matlab编写,采用CV模型,卡尔曼跟踪,有轨迹模拟,给出了跟踪的误差 目标跟踪,采用CV模型,卡尔曼滤波,给出模拟结果和跟踪结果,给出误差分析(Target tracking program, using matlab prepared, using the CV model, Kalman tracking, trajectory simulations have given a tracking error target tracking, using the CV model, Kalman filter, and track the results of the simulation results are given, error analysis is given)

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)

摄像头录制功能

建立了普通话语音性别数据库,提出联合梅尔频率频谱系数(Mel2f requency Cep st rum Coefficient s , MFCC) 的特征提取方法和支持向量机(Support Vector Machine , SVM) 的分类方法进行说话人性别识别,并与其它分类方法进行比较。(A Chinese speech ( mandarin ) database was established for speaker s gender recognition. A combination met hod is p roposed for gender recognition of speaker s based on support vector machine and Mel2f requency cep st rum coefficient s (MFCC) for classification and feat ure ext raction respectively.)

对于一张8位灰度图像lena.bmp 1）运用4×4抖动矩阵，生成对应抖动图像 2）生成有序抖动图像 3）对于一张24位彩色图像，生成4×4抖动图像( For a 8-bit gray image (lena.bmp) 1）Use a dithering matrix (4*4), generate the dithered image. 2) Generate the ordered ditering image (4*4). 3) For a 24-bit color image, generate the dithered image (4*4). )