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Jingdong book

张量投票方法及其在机器视觉中的应用

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Jingdong book

张量投票方法及其在机器视觉中的应用

Name: 张量投票方法及其在机器视觉中的应用
Brand: Jingdong book
SKU: 3118206911
Price: 58.77 USD
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Content Description

《张量投票方法及其在机器视觉中的应用》从张量投票方法的基础开始，系统介绍算法的原理、流程、应用和改进，内容包括六章。第一章是引言；第二章介绍一些与张量投票相关的数学知识；第三章是对张量投票方法的全面描述，是全书的中心和后续章节的基石；第四章和第五章分别是该方法在图像处理和机器视觉领域的应用，从而加强对该方法的理解和运用；第六章展现一些基础性的改进工作；*后是后记，包含对张量投票的哲学思考。
《张量投票方法及其在机器视觉中的应用》可供从事图像处理或机器视觉相关学科专业的本科生、研究生等学习，也可供相关科研工作者和工程技术人员等参考。

Catalogue

《信息科学技术学术著作丛书》序
序
前言
符号表
第1章概述
1．1 引言
1．2 张量投票方法的历史沿革
1．3 相关工作
参考文献

第2章张量相关知识
2．1 引言
2．2 张量的基本概念和性质
2．2．1 张量投票中的张量定义
2．2．2 张量的性质
2．2．3 张量的矩阵表示
2．3 张量投票中的数学知识
2．4 本章小结
参考文献

第3章张量投票方法
3．1 引言
3．2 底层处理
3．2．1 取向的定义和表示方法
3．2．2 取向估计原理
3．2．3 现有方法
3．2．4 基于张量的取向估计方法的理论框架
3．3 数据表示
3．3．1 二维数据表示
3．3．2 三维数据表示
3．3．3 张量维数的选择
3．3．4 张量表示分析
3．4 投票域计算
3．4．1 连续律
3．4．2 设计规则
3．4．3 计算公式
3．5 投票过程
3．5．1 投票域的旋转
3．5．2 投票的叠加
3．5．3 投票的极性
3．6 特征提取
3．6．1 投票解释
3．6．2 曲线／曲面提取
3．7 计算复杂度
3．8 比较与分析
3．8．1 张量投票与双弧插值算法
3．8．2 张量投票与Hough变换
3．8．3 张量投票与欧拉弹性模型
3．8．4 张量投票与随机修复场模型
3．9 本章小结
参考文献

第4章张量投票在图像处理领域的应用
4．1 线／角点检测
4．1．1 相关工作
4．1．2 方法描述
4．1．3 实验结果示例
4．2 端点提取
4．2．1 方法描述
4．2．2 实验结果示例
4．3 边界增强／提取／修复
4．3．1 相关工作
4．3．2 方法描述
4．3．3 实验结果示例
4．4 取向估计
4．4．1 方法描述
4．4．2 实验结果示例
4．5 图像灰度／颜色校正
4．5．1 相关工作
4．5．2 方法描述
4．5．3 实验结果示例
4．6 文字预处理
4．6．1 相关工作
4．6．2 方法描述
4．7 图像压缩
4．7．1 相关工作
4．7．2 方法描述
4．7．3 实验结果示例
4．8 图像去噪
4．8．1 相关工作
4．8．2 方法描述
4．9 图像修复
4．9．1 相关工作
4．9．2 方法描述
4．9．3 实验结果示例
4．10 小结与分析
参考文献

第5章张量投票在机器视觉领域的应用
5．1 立体匹配
5．1．1 相关工作
5．1．2 方法描述
5．1．3 实验结果示例
5．2 阴影恢复形状
5．2．1 相关工作
5．2．2 方法描述
5．2．3 实验结果示例
5．3 医学图像的三维可视化
5．3．1 相关工作
5．3．2 方法描述
5．3．3 实验结果示例
5．4 流可视化
5．4．1 相关工作
5．4．2 方法描述
5．4．3 实验结果示例
5．5 涡流检测
5．5．1 相关工作
5．5．2 方法描述
5．5．3 实验结果示例
5．6 三维曲线／曲面提取
5．6．1 相关工作
5．6．2 方法描述
5．6．3 实验结果示例
5．7 地形可视化
5．7．1 相关工作
5．7．2 方法描述
5．7．3 实验结果示例
5．8 断层检测
5．8．1 三维地震数据与断层检测的关系
5．8．2 相关工作
5．8．3 方法描述
5．8．4 实验结果示例
5．9 光流场计算
5．9．1 相关工作
5．9．2 方法描述
5．9．3 实验结果示例
5．10 目标跟踪
5．10．1 相关工作
5．10．2 方法描述
5．10．3 实验结果示例
5．11 本章小结
参考文献

第6章张量投票方法的改进
6．1 引言
6．1．1 理论研究
6．1．2 算法改进
6．1．3 应用拓展
6．2 底层处理——取向估计
6．2．1 计算原理
6．2．2 实验验证与结果分析
6．3 投票域优化
6．3．1 尺度参数的选取
6．3．2 投票域的简化和调整
6．3．3 投票域的变形
6．4 投票过程的调整
6．4．1 迭代的引入
6．4．2 迭代产生的问题分析
6．4．3 迭代的改进
6．5 投票解释——特征显著性度量
6．5．1 曲线特征显著度
6．5．2 含噪曲线特征显著度
6．5．3 角点／交汇点特征显著度
6．6 本章小结
参考文献
附录二维张量投票算法的Matlab代码
后记

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