MRIbrainscan

图像拼接 sift 特征点，两幅图像进行拼配 拼接，先找找出特征点匹配(The image stitching， sift feature points, two images blending splicing find someone to identify the characteristics of point matching)

实现一个高精度指针仪表读数自动识别系统．用数码摄像头采集仪表的图像，然后利用数字图像处理技术识别刻度和指针，根据指针和刻度的相对位置计算指针读数值．使用条件霍夫变换（Constrained HOUGH Transfer）和中心投影分析法实现刻度的全自动识别，采用快速中心投影法进行指针检测与识别，识别速度达到68ms．实验结果表明该方法比传统方法速度快、精度高，系统读数平均误差仅为0．016％(To achieve a high precision automatic identification system pointer meter reading. Instrument with a digital camera capture images, then using digital image processing technology to identify scale and pointer, pointer and scale according to the relative position of the pointer readings calculated. Use Hough transform (Constrained HOUGH Transfer) and center projection analysis method to achieve scale automatic identification method using fast center projection target detection and recognition, recognition speed of 68ms. Experimental results show that faster than traditional methods, high accuracy, the system average error of only 0.016 of reading)

Matlab图像处理教程简易教程 - /1、图像的读取和显示 /2、图像的点运算 /3、图像的几何变换 /4、空间域图像增强 /5、频率域图像增强 /6、彩色图像(Matlab image processing tutorial Easy Tutorial-/1, read and display image/2 image point operations/3, the image of geometric transformation/4 spatial domain image enhancement/5, the frequency domain image enhancement/6 color image)

说明：  自己写的位图三态按钮还添加了按钮声音,对自己制作图形界面有很大帮助(Write your own bitmap three-state buttons to add the button sounds right to produce their own graphical interface helps a lot)

matlab代码实现的MSR图像增强，有参考图片(MSR image enhancement matlab code, reference picture)

针对彩色图像的局部直方图均衡化，可以较好的增强图像细节(poshe,it can enhancements the detail of the image )

说明：  基于matlab的钢筋计数方法，有ui界面(MATLAB-based steel bar counting method with UI interface)

利用霍夫曼编码对图像进行编码及解码，计算霍夫曼编码效率(huffman encode and decode)

本书系统地介绍了图像处理与识别的基本原理、典型方法和实用技术。全书共分12章，第1章～第6章是图像处理与识别的基础内容，包括图像科学综述、MATLAB语言图像编程、图像增强、图像分割、图像特征提取和图像识别；第7章～第10章是图像处理与识别的工程实例，涵盖了医学图像处理、文字识别和自导引小车路径识别等应用实例，并结合理论算法，提供了大量MATLAB代码程序，以帮助读者掌握如何使用MATLAB语言快速进行算法的仿真、调试和估计等方法。第11章～第12章，是两个综合性较强的实例，分别是Visual C++实现的基于神经网络的文字识别系统和车牌定位系统。 本书附带的光盘给出了各个章节列举的实例的源代码，同时赠送了28个常用数字图像处理算法的Visual C++代码实现。 本书讲解深入浅出，实例程序丰富，注重理论与实践相结合。本书可作为计算机应用、自动化、图像处理与模式识别、机电一体化专业的高年级本科生或研究生的参考书，也可供从事图像处理与识别的研究人员和工程技术人员阅读参考。(This book introduces the basic principles of image processing and recognition of the typical methods and practical skills . The book is divided into 12 chapters , Chapter 1- Chapter 6 is the basis of the content of image processing and recognition , including images scientific overview , MATLAB programming language images, image enhancement, image segmentation, image feature extraction and image recognition Chapter 7- Section Chapter 10 is a project example image processing and recognition , covering the medical image processing, character recognition and self- guided trolley path recognition example , the combination of theory and algorithms, for a lot of MATLAB code procedures to help readers learn how to use MATLAB language fast simulation , debugging and estimation methods algorithm. Chapter 11- Chapter 12 , are two examples of highly integrated , namely Visual C++ implementation based on neural network character recognition system and a license plate positioning system. The book)

以心电信号为例，利用小波变换模极大重建原信号(Reconstruction of the original signal using wavelet transform modulus maxima)