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Hypothesizing and testing geometric properties of image data

✍ Scribed by Kenichi Kanatani

Book ID
103997013
Publisher
Elsevier Science
Year
1991
Weight
921 KB
Volume
54
Category
Article
ISSN
1049-9660

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✦ Synopsis

A general formulation for detecting geometric configurations of inaccurate image data is presented. The basic principle is hypofhesizing and testing: We first estimate an ideal geometric configuration that supposedly exists, and then check to what extent the original edge data must be displaced in order to support the hypothesis. All types of tests are reduced to computing a single measure of edge displacement, which provides a universal measure of confidence applicable to all types of decision-making. All the procedures are described by explicit algebraic expressions in N-vectors from the viewpoint of computational projective geometry.

πŸ“œ SIMILAR VOLUMES

Statistical Foundation for Hypothesis Te
Statistical Foundation for Hypothesis Testing of Image Data
✍ K. Kanatani πŸ“‚ Article πŸ“… 1994 πŸ› Elsevier Science βš– 932 KB

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 eval