Rectilinearity measurements for polygons

The paper introduces a shape measure intended to describe the extent to which a closed polygon is rectilinear. Other than somewhat obvious measures of rectilinearity (e.g., the sum of the differences of each corner's angle from multiples of 90/spl deg/), there has been little work in deriving a...

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Bibliographic Details
Published in:IEEE transactions on pattern analysis and machine intelligence 2003-09, Vol.25 (9), p.1193-1200
Main Authors: Zunic, J., Rosin, P.L.
Format: Article
Language:English
Subjects:
Application software
Buildings
Computer vision
Footprints
Ground plane
Image processing
Image recognition
Image reconstruction
Intelligence
Invariants
Pattern analysis
Polygons
Reconstruction
Rotation measurement
Shape measurement
Stereo image processing
Stereo vision
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Summary:The paper introduces a shape measure intended to describe the extent to which a closed polygon is rectilinear. Other than somewhat obvious measures of rectilinearity (e.g., the sum of the differences of each corner's angle from multiples of 90/spl deg/), there has been little work in deriving a measure that is straightforward to compute, is invariant under scale, rotation, and translation, and corresponds with the intuitive notion of rectilinear shapes. There are applications in a number of different areas of computer vision and photogrammetry. Rectilinear structures often correspond to human-made objects and are therefore justified as attentional cues for further processing. For instance, in aerial image processing and reconstruction, where building footprints are often rectilinear on the local ground plane, building structures, once recognized as rectilinear, can be matched to corresponding shapes in other views for stereo reconstruction. Perceptual grouping algorithms may seek to complete shapes based on the assumption that the object in question is rectilinear. Using the proposed measure, such systems can verity this assumption.
ISSN:0162-8828
1939-3539
DOI:10.1109/TPAMI.2003.1227997