数字图像处理与机器视觉-VisualC++与Matlab第二版随书源代码 作者:张铮 徐超 等 亲测可用

上传者: jam8139 | 上传时间: 2025-06-24 13:34:49 | 文件大小: 34.25MB | 文件类型: 7Z
《数字图像处理与机器视觉-VisualC++与Matlab第二版随书源代码》是由张铮、徐超等专家编著的一本专业书籍,主要涵盖了数字图像处理和机器视觉领域的核心技术,并结合Visual C++和Matlab两个强大的编程环境进行深入探讨。这本书的随书源代码提供了丰富的实践案例,便于读者理解和掌握相关知识。 1. 数字图像处理:这部分内容涉及图像的基本概念,包括像素、图像的数字化、颜色模型(如RGB、灰度、索引色等),以及图像的常见操作,如平移、旋转、缩放、滤波(如均值滤波、高斯滤波、中值滤波)等。此外,还包括图像增强、图像分割、直方图处理、边缘检测(如Sobel、Prewitt、Canny算法)等技术,这些都是图像处理的基础。 2. 机器视觉:机器视觉是人工智能的重要分支,它涉及到特征提取、模板匹配、物体识别、形状分析等高级应用。书中可能通过实例介绍了如何利用机器学习方法(如支持向量机SVM、神经网络)进行图像分类和识别,以及如何运用OpenCV等库来实现复杂的视觉任务。 3. Visual C++:C++是一种强大的面向对象的编程语言,特别适合开发高性能的应用程序。在图像处理和机器视觉领域,C++可以提供高效的数据结构和算法实现。书中可能讲解了如何使用MFC(Microsoft Foundation Classes)构建图形用户界面,以及如何使用OpenCV库在C++中进行图像处理。 4. Matlab:Matlab是一种流行的科学计算环境,对于图像处理和机器视觉有专门的Image Processing Toolbox和Computer Vision Toolbox。这些工具箱提供了丰富的函数,简化了图像处理和视觉算法的开发。书中可能介绍了如何使用Matlab编写图像处理脚本,以及如何调用预定义的函数进行复杂计算。 5. 源代码文件:压缩包中的各个章节文件(如chapter6至chapter17)包含了与书中各个章节对应的源代码,读者可以通过运行这些代码来加深对理论知识的理解。例如,"VS2010和2012版本之间的转换说明.doc"可能是指导读者如何在不同Visual Studio版本之间迁移和兼容项目的文档。 这本书结合了理论与实践,旨在帮助读者从基础到高级全面掌握数字图像处理和机器视觉的知识,同时提供实用的编程经验,无论你是初学者还是经验丰富的开发者,都能从中受益。通过实际运行书中提供的源代码,读者可以更直观地了解和应用这些技术,从而提升自己的技能水平。

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