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Jingdong book

机器视觉检测理论与算法

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Books Computers & Internet Programming Language and Programming

Jingdong book

机器视觉检测理论与算法

Name: 机器视觉检测理论与算法
Brand: Jingdong book
SKU: 3118212111
Price: 48.22 USD
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Content Description

《机器视觉检测理论与算法》首先系统介绍了视觉检测算法的发展及其研究现状，总结了视觉检测软件系统的体系结构与识别算法流程，然后以图像预处理、图像分割、图像变换、特征提取、图像匹配、图像分析与分类这一视觉检测流程为主线，通过粘扣带、网孔织物、坯布、导爆管、电子元器件、电子接插件、FPc补强片、汽车锁扣、列车车辆等多类产品的视觉检测应用实例以及各种算法的实验对比分析，揭示各视觉检测算法的适用场合与优缺点，为视觉检测系统的开发以及新算法的设计提供相关指导。
本书可作为高等院校计算机、测控和机电等专业的本科生和研究生的学习参考书，也可供相关领域技术人员阅读。

Catalogue

前言
第1章机器视觉检测概述
1.1 机器视觉应用与发展
1.1.1 机器视觉发展现状
1.1.2 机器视觉应用分类
1.1.3 机器视觉应用领域
1.2 视觉检测原理与软件体系
1.2.1 视觉检测工作原理
1.2.2 视觉检测中图像处理流程
1.2.3 视觉检测软件体系
1.3 视觉检测算法的研究现状
1.3.1 预处理算法与应用
1.3.2 图像分割算法与应用
1.3.3 图像变换算法与应用
l.3.4 图像特征提取与匹配
1.3.5 图像分析与分类
1.4 本书的组织结构及机器视觉案例简介
1.4.1 本书的组织结构
1.4.2 机器视觉案例简介
第2章图像预处理
2.1 图像滤波
2.1.1 高斯滤波
2.1.2 均值滤波
2.1.3 中值滤波
2.1.4 粘扣带疵点视觉检测的图像滤波
2.1.5 导爆管视觉检测的图像滤波
2.2 图像锐化
2.2.1 图像梯度锐化算法原理
2.2.2 汽车锁扣铆点视觉测量的边缘锐化
2.3 图像增强
2.3.1 灰度变换
2.3.2 直方图增强
2.3.3 电子元器件视觉检测的图像增强
第3章图像分割
3.1 边缘检测
3.1.1 一阶微分边缘算子
3.1.2 二阶微分边缘算子
3.1.3 形态学边缘检测
3.1.4 粘扣带疵点视觉检测的边缘检测
3.1.5 网孔织物质量视觉检测的边缘检测
3.1.6 导爆管视觉检测的边缘检测
3.1.7 电子元器件视觉检测的边缘检测
3.2 基于先验知识的ROI提取
3.2.1 ROI设定方法
3.2.2 先验知识的表示
3.2.3 FPC补强片缺陷检测的轮廓掩模
3.2.4 汽车锁扣铆点视觉测量的铆点ROI提取
3.2.5 TFDS挡键故障识别的ROI定位
3.3 直方图反向投影
3.3.1 基于灰度的直方图反向投影算法
3.3.2 基于直方图反向投影的坯布疵点定位
3.3.3 基于灰度共生矩阵与反向投影的坯布疵点定位
3.4 阈值分割
3.4.1 全局阈值分割
3.4.2 局部闽值分割
3.4.3 导爆管视觉检测的阈值分割
3.4.4 坯布疵点视觉检测的阈值分割
3.4.5 网孔织物质量视觉检测的阈值分割
3.4.6 FPC补强片缺陷检测的阈值分割
3.4.7 TFDS挡键故障识别的阈值分割
3.5 轮廓算法
3.5.1 轮廓提取
3.5.2 连通标记
3.5.3 边界追踪
3.5.4 轮廓的几何特征
3.5.5 网孔织物质量视觉检测的网孔轮廓标记
3.5.6 电子接插件视觉检测的：Pin轮廓定位
3.5.7 FPC补强片缺陷检测的缺陷轮廓特征
第4章图像变换
4.1 形态学处理
4.1.1 腐蚀与膨胀
4.1.2 开运算与闭运算
4.1 13形态骨架提取
4.1.4 FPC补强片激光测高的光斑定位
4.2 几何变换
4.2.1 平移、缩放与旋转
4.2.2 仿射变换
4.2.3 汽车锁扣铆点视觉测量的仿射变换
4.3 图像轮廓拟合
4.3.1 直线拟合
4.3.2 圆的拟合
4.3.3 FPC补强片激光测高的光斑椭圆拟合
4.3.4 TFDS零件轮廓的组合图元识别
4.4 图像的直一极坐标变换
第5章特征提取与图像匹配
5.1 基于灰度的特征提取与匹配
5.1.1 基于灰度的模板匹配
5.1.2 高斯金字塔匹配
5.1.3 TFDS截断塞门手把的灰度模板匹配
5.2 基于不变矩的特征提取与匹配
5.2.1 不变矩特征
5.2.2 基于不变矩的匹配算法
5.2.3 TFDS截断塞门手把的不变矩变步长匹配
5.3 基于形状的特征提取与匹配
5.3.1 基于几何形状特征的TFDS截断塞门手把匹配
5.3.2 基于改进形状上下文的TFDS挡键故障识别
5.3.3 基于角度与尺度混合描述子的TFDS集尘器匹配
5.3.4 基于改进高度函数的T：FDS截断塞门手把匹配
第6章图像分析与分类
6.1 图像特征分类
6.1.1 颜色特征
6.1.2 纹理特征
6.1.3 形状特征
6.1.4 空间关系特征
6.2 SVM分类
6.2.1 基于SVM的视觉检测分类算法
6.2.2 坯布视觉检测中基于SVM的疵点分类
6.3 BP神经网络分类
6.3.1 基于BP神经网络的视觉检测分类算法
6.3.2 坯布视觉检测中基于BP神经网络的疵点分类
参考文献

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