From Gestalt Theory to Image Analysis: A Probabilistic Approach
From Gestalt Theory to Image Analysis: A Probabilistic Approach
复制标题
DOI：
--
复制
发表时间：
2007-12
期刊：
影响因子：
3.6
通讯作者：
A. Desolneux;L. Moisan;J. Morel
中科院分区：
文献类型：
--
作者：
A. Desolneux;L. Moisan;J. Morel
这本书向读者介绍了计算机视觉的最新理论，产生了分析数字图像的基本技术。这些技术的灵感来自于格式塔理论的数学形式化。格式塔理论从未被形式化，它是1923年至1975年间发展起来的一个严格的视觉心理学领域。从数学的角度来看，最接近它的领域是随机几何，涉及基本的概率和统计，在图像分析的背景下。作者维护了一个公共软件，MegaWave，其中包含了书中开发的大多数图像分析技术的实现。这本书是为研究人员和工程师编写的。它在数学上是独立的，只需要概率论和微积分的基本概念。
This book introduces the reader to a recent theory in Computer Vision yielding elementary techniques to analyse digital images. These techniques are inspired from and are a mathematical formalization of the Gestalt theory. Gestalt theory, which had never been formalized is a rigorous realm of vision psychology developped between 1923 and 1975. From the mathematical viewpoint the closest field to it is stochastic geometry, involving basic probability and statistics, in the context of image analysis. The authors maintain a public software, MegaWave, containing implementations of most of the image analysis techniques developped in the book. The book is intended for researchers and engineers. It is mathematically self-contained and requires only the basic notions in probability and calculus.