MRI-brain-segmentation-using-FCM

计算机视觉中得八点算法，采用SVD分解最小二乘解来求基本矩阵，这是模拟仿真实验程序。(Was 8:00 in computer vision algorithms, using SVD decomposition least-squares solution to seek the fundamental matrix, which is simulation, experimental procedure.)

光流法、帧间差分法、高斯背景模型差分法，在opencv环境下实现运动目标检测(moving objective detection matlab)

本程序集合了互信息配准，PV差值，powell算法，基于小波变换的图像融合的一整套算法。只需要在GUI界面输入两幅图像，即可自动完成图像的配准融合。程序包含Matlab源代码。用Matlab打开imagefusion.m，即会弹出gui界面。融合前要输入参考和浮动图像。图像要求像素的 长＊宽 一样。否则会报错。程序只能处理灰度图像，彩色图像也会转化成灰度图像处理。程序代码已经有详细的注释，方便读者理解。(The procedures set of mutual information, PV difference, powell algorithm, based on wavelet transform image fusion set of algorithms. Only need to enter the two images in the GUI interface, you can automatically complete the image registration fusion. Program contains Matlab source code. Using Matlab open imagefusion.m, gui interface will pop up. Fusion before the input reference and floating images. Image requires the same pixel length* width. Otherwise incorrect. Can only handle grayscale images, color images into gray image processing also. Program code has detailed notes, to facilitate understanding.)

舌像的梯度提取，然后进行分水岭分割，最后进行邻近区域合并，得到舌体图像。(tongue-image s watershed segmentation based on its gradient change.)

matlab编写的CT图像的滤波反投影程序(matlab prepared CT images of the filtered back-projection program)

说明：  基于IHS融合算法的多光谱与全色图像融合代码，使用于融合ETM+遥感图像(IHS-based multi-spectral and panchromatic image fusion code)

Level set solver for two phases flow

一种简单高效地基于压缩感知的跟踪算法。首先利用符合压缩感知RIP条件的随机感知矩对多尺度图像特征进行降维，然后在降维后的特征上采用简单的朴素贝叶斯分类器进行分类。该跟踪算法非常简单，但是实验结果很鲁棒，速度大概能到达40帧/秒(A simple and efficient tracking algorithm based on compressed sensing. Firstly, with the random sensing matrix compressed sensing RIP conditions for multi-scale image feature dimension reduction, and then use the naive Bias classifier simple classification in the feature reduction after the. The tracking algorithm is very simple, but the results are robust, speed can reach 40 frames per second)

C# 界面皮肤

说明：  非常详细的一篇论文，仔细介绍了手指静脉识别的的全过程(A very detailed paper, carefully introduced the finger vein identification process)