A continuous probabilistic framework for image matching
A continuous probabilistic framework for image matching
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DOI：
10.1006/cviu.2001.0946
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发表时间：
2001-12-01
影响因子：
4.5
通讯作者：
Ridel, L
中科院分区：
文献类型：
--
作者：
Greenspan, H;Goldberger, J;Ridel, L
本文描述了一种概率图像匹配方案，其中图像表示是连续的，并且在连续域中定义了相似性度量和距离计算。每个图像首先被表示为高斯混合分布，图像通过分布之间相似性的概率度量进行比较和匹配。一个通用的概率和连续框架被应用于表示以及匹配过程，确保整个系统在理论上具有吸引力。研究了匹配结果，并演示了在图像检索系统中的应用。(C) 2001 Elsevier Science（美国）
In this paper we describe a probabilistic image matching scheme in which the image representation is continuous and the similarity measure and distance computation are also defined in the continuous domain. Each image is first represented as a Gaussian mixture distribution and images are compared and matched via a probabilistic measure of similarity between distributions. A common probabilistic and continuous framework is applied to the representation as well as the matching process, ensuring an overall system that is theoretically appealing. Matching results are investigated and the application to an image retrieval system is demonstrated. (C) 2001 Elsevier Science (USA).