m_map用法详解

实现bmp图像读入和写出，彩色图像灰度化，直方图均衡化(Implement bmp image read and write, color image graying, histogram equalization)

对形图像的经过边缘提取后得到的二值图像边缘进行细化，提取单像素的边缘，使得边缘是成为清楚的单像素的边缘。(After images of the shape after the edge extraction of the binary image to refine the edge, the edge extraction of a single pixel, making the edge is to be clear of the edge of a single pixel.)

很好用的图像分割方法，大家可以试一下，我运行过了(Very good segmentation method, very useful, you can have a try, I used the effect is very good)

说明：  Invensense公司的modm实例代码example。 初始化以及IIC的引用示例。(The example of modm from Invensense. IIC initiation and configuration initiation.)

说明：  通过websocket接收h264裸流后，在web端解析播放(After receiving the bare stream of h264 through websocket, it is parsed and played on the web side)

2d convolution on image

此文件一共包含3个m文件。第一个文件的功能是绘制一个二值图像，并显示其傅立叶幅度谱。文件2功能是设计频域理想低通滤波器，并加以验证：读入一个二值图像(cameraman.tif)加噪声后在频域进行低通滤波观察滤波后的图像效果。文件3的功能是对图像eight.tif加入椒盐噪声后，实现Butterworth低通滤波.(This file contains 3 m documents. Functions of first file is to draw a binary image, and displays its Fourier amplitude spectrum. Document 2 is designed to function a frequency domain ideal low-pass filter , and verified it: reading a binary image (cameraman.tif) plus noise on it and smoothing it in the frequency domain using low-pass filtering.The filtered effect will be observed by displaying image.Document 3 is designed to read a binary image(eight.tif) and add salt and pepper noise on it, realized frequence domain Butterworth low-pass filter.)

文简要介绍了指纹识别的基本步骤，分别是指纹图像预处理、指纹特征提取、指纹匹配(This paper briefly introduces the basic steps of fingerprint recognition, which are fingerprint image preprocessing, fingerprint feature extraction and fingerprint matching)

说明：  使用MATLAB生成二维voronoi图的代码，可以用作后续二维voronoi的多晶模型建立(The code of two-dimensional Voronoi diagram generated by MATLAB can be used to build the polycrystalline model of two-dimensional voronoi.)

我的毕业设计，用matlab编的关键帧提取的代码，参考了光流法的代码。是基于帧差的欧式距离，均值，方差，差异系数下的关键帧提取。代码调试通过，运行结果理想，与大家分享下。(I graduated from design, matlab key frame extraction for the code, with reference to code optical flow method. Frame difference is based on the Euclidean distance, the mean, variance, difference coefficient under the key frame extraction. Debugging through the code, run the results are satisfactory, the next to share with you.)