by Marji, M, Klette, R and Siy, P
Abstract:
There are several algorithms for curve partitioning using the arc-chord distance formulation, where a chord whose associated arc spans k pixels is moved along the curve and the distance from each border pixel to the chord is computed. The scale of the corners detected by these algorithms depends on the choice of integer k. Without a priori knowledge about the curve, it is difficult to choose a k that yields good results. This paper presents a modified method of this type that can tolerate the effects of an improper choice of k to an acceptable degree. © Springer-Verlag 2004.
Reference:
Corner Detection and Curve Partitioning Using Arc-Chord Distance (Marji, M, Klette, R and Siy, P), In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 3322, 2004.
Bibtex Entry:
@article{marji2004cornerdistance,
author = "Marji, M and Klette, R and Siy, P",
journal = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "512--521",
title = "Corner Detection and Curve Partitioning Using Arc-Chord Distance",
volume = "3322",
year = "2004",
abstract = "There are several algorithms for curve partitioning using the arc-chord distance formulation, where a chord whose associated arc spans k pixels is moved along the curve and the distance from each border pixel to the chord is computed. The scale of the corners detected by these algorithms depends on the choice of integer k. Without a priori knowledge about the curve, it is difficult to choose a k that yields good results. This paper presents a modified method of this type that can tolerate the effects of an improper choice of k to an acceptable degree. © Springer-Verlag 2004.",
issn = "0302-9743",
eissn = "1611-3349",
language = "eng",
}