IVS

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)

对测井曲线进行重构的程序，可以充分利用测井特征曲线所反应的岩性特征信息，完成多信息的融合(Log curve reconstruction procedures)

DIX公式优化求解层速度，使得速度变得更加平滑。(DIX formula optimization solution velocity, making speed becomes smoother.)

本程序基于近景摄影测量，单片空间后方交会算法完成，用C++代码编写，内含有样本数据，以供试验。运行正常，注释完整。(This procedure based on the close shot photogrammetry, monolithic space resection algorithm, contains sample data, and written in c++ code for test. Running normally, notes complete.)

一个很好类子来说明类模板的使用，可以比较明了类模板的使用方法，最好进行单步调试(use of class template )

卡尔曼滤波算法，opencv代码，鼠标跟踪(Kalman filter algorithm, opencv code, mouse tracking)

针对大尺度图像配准和不同传感器图像配准问题, 介绍了一种基于 SIFT 的图像配准方 法。(For large-scale image registration and image registration problem from different sensors, introduces a SIFT-based image registration method.)

1 完成图象处理的基本功能2：二值化、边缘检测、滤波。 2 熟悉dc的部分常用功能，学习图标控制弹出框。(a complete image processing of the two basic functions : values, edge detection, filtering. 2 familiar with the dc part of the commonly used function, learning to control pop icon frame.)

红外图像的亚像素边缘检测，检测边缘，用于图像配准。(Infrared image of the sub-pixel edge detection, edge detection for image registration.)

Code for make histogram of image