✦ LIBER ✦

Statistical Foundation for Hypothesis Testing of Image Data

✍ Scribed by K. Kanatani

Publisher: Elsevier Science
Year: 1994
Weight: 932 KB
Volume: 60
Category: Article
ISSN: 1049-9660
DOI: 10.1006/ciun.1994.1064

No coin nor oath required. For personal study only.

✦ Synopsis

A statistical foundation is given to the problem of hypothesizing and testing geometric properties of image data heuristically derived by Kanatani (CVGIP: Image Understanding 54 (1991), 333-348). Points and lines in the image are represented by " (\mathrm{N})-vectors" and their reliability is evaluated by their "covariance matrices". Under a Gaussian approximation of the distribution, the test takes the form of a (\boldsymbol{\chi}^{2}) test. Test criteria are explicitly stated for model matching and testing edge groupings, vanishing points, focuses of expansion, and vanishing lines. e 1994 Academic Press, Inc.

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