Foundations of Computer Vision: Computational Geometry, Visual Image Structures and Object Shape Detection (Intelligent Systems Reference Library)

This book introduces the fundamentals of computer vision (CV), with a focus on extracting useful information from digital images and videos. Including a wealth of methods used in detecting and classifying image objects and their shapes, it is the first book to apply a trio of tools (computational geometry, topology and algorithms) in solving CV problems, shape tracking in image object recognition and detecting the repetition of shapes in single images and video frames. Computational geometry provides a visualization of topological structures such as neighborhoods of points embedded in images, while image topology supplies us with structures useful in the analysis and classification of image regions. Algorithms provide a practical, step-by-step means of viewing image structures.

The implementations of CV methods in Matlab  and Mathematica, classification of chapter problems with the symbols (easily solved) and (challenging) and its extensive glossary of key words, examples and connections with the fabric of CV make the book an invaluable resource for advanced undergraduate and first year graduate students in Engineering, Computer Science or Applied Mathematics.

It offers insights into the design of CV experiments, inclusion of image processing methods in CV projects, as well as the reconstruction and interpretation of recorded natural scenes.

本書介紹了計算機視覺（CV）的基礎知識，重點是從數字圖像和視頻中提取有用的信息。該書包含了在檢測和分類圖像對象及其形狀方面使用的眾多方法，是第一本應用計算幾何、拓撲和算法三種工具來解決CV問題的書籍，包括圖像對象識別中的形狀跟踪以及單幅圖像和視頻幀中形狀的重複檢測。計算幾何提供了圖像中嵌入的點的鄰域等拓撲結構的可視化，而圖像拓撲則為我們提供了在圖像區域分析和分類中有用的結構。算法提供了一種實用的、逐步的方法來查看圖像結構。

本書在Matlab和Mathematica中實現了CV方法，通過符號（易解決）和（具有挑戰性）對章節問題進行分類，並提供了詳盡的關鍵詞詞匯表、示例和與CV相關的連接，使本書成為工程、計算機科學或應用數學的高年級本科生和研究生的寶貴資源。

本書提供了關於CV實驗設計、將圖像處理方法納入CV項目以及對記錄的自然場景進行重建和解釋的見解。