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This paper addresses the problem of detecting digital line components in a given binary image consisting of *n* black dots arranged over *N* *N* integer grids. The most popular method in computer vision for this purpose is the one called Hough Transform which transforms each black point to a sinusoidal curve to detect digital line components by voting on the dual plane. We start with a definition of a line component to be detected and present several different algorithms based on the definition. The one extreme is the conventional algorithm based on voting on the subdivided dual plane while the other is the one based on topological walk on an arrangement of sinusoidal curves defined by the Hough transform. Some intermediate algorithm based on half-planar range counting is also presented. Finally, we discuss how to incorporate several practical conditions associated with minimum density and restricted maximality.

- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E84-A No.5 pp.1120-1129

- Publication Date
- 2001/05/01

- Publicized

- Online ISSN

- DOI

- Type of Manuscript
- Special Section PAPER (Special Section on Discrete Mathematics and Its Applications)

- Category

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Tetsuo ASANO, Koji OBOKATA, Takeshi TOKUYAMA, "On Detecting Digital Line Components in a Binary Image" in IEICE TRANSACTIONS on Fundamentals,
vol. E84-A, no. 5, pp. 1120-1129, May 2001, doi: .

Abstract: This paper addresses the problem of detecting digital line components in a given binary image consisting of *n* black dots arranged over *N* *N* integer grids. The most popular method in computer vision for this purpose is the one called Hough Transform which transforms each black point to a sinusoidal curve to detect digital line components by voting on the dual plane. We start with a definition of a line component to be detected and present several different algorithms based on the definition. The one extreme is the conventional algorithm based on voting on the subdivided dual plane while the other is the one based on topological walk on an arrangement of sinusoidal curves defined by the Hough transform. Some intermediate algorithm based on half-planar range counting is also presented. Finally, we discuss how to incorporate several practical conditions associated with minimum density and restricted maximality.

URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e84-a_5_1120/_p

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@ARTICLE{e84-a_5_1120,

author={Tetsuo ASANO, Koji OBOKATA, Takeshi TOKUYAMA, },

journal={IEICE TRANSACTIONS on Fundamentals},

title={On Detecting Digital Line Components in a Binary Image},

year={2001},

volume={E84-A},

number={5},

pages={1120-1129},

abstract={This paper addresses the problem of detecting digital line components in a given binary image consisting of *n* black dots arranged over *N* *N* integer grids. The most popular method in computer vision for this purpose is the one called Hough Transform which transforms each black point to a sinusoidal curve to detect digital line components by voting on the dual plane. We start with a definition of a line component to be detected and present several different algorithms based on the definition. The one extreme is the conventional algorithm based on voting on the subdivided dual plane while the other is the one based on topological walk on an arrangement of sinusoidal curves defined by the Hough transform. Some intermediate algorithm based on half-planar range counting is also presented. Finally, we discuss how to incorporate several practical conditions associated with minimum density and restricted maximality.

keywords={},

doi={},

ISSN={},

month={May},}

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TY - JOUR

TI - On Detecting Digital Line Components in a Binary Image

T2 - IEICE TRANSACTIONS on Fundamentals

SP - 1120

EP - 1129

AU - Tetsuo ASANO

AU - Koji OBOKATA

AU - Takeshi TOKUYAMA

PY - 2001

DO -

JO - IEICE TRANSACTIONS on Fundamentals

SN -

VL - E84-A

IS - 5

JA - IEICE TRANSACTIONS on Fundamentals

Y1 - May 2001

AB - This paper addresses the problem of detecting digital line components in a given binary image consisting of *n* black dots arranged over *N* *N* integer grids. The most popular method in computer vision for this purpose is the one called Hough Transform which transforms each black point to a sinusoidal curve to detect digital line components by voting on the dual plane. We start with a definition of a line component to be detected and present several different algorithms based on the definition. The one extreme is the conventional algorithm based on voting on the subdivided dual plane while the other is the one based on topological walk on an arrangement of sinusoidal curves defined by the Hough transform. Some intermediate algorithm based on half-planar range counting is also presented. Finally, we discuss how to incorporate several practical conditions associated with minimum density and restricted maximality.

ER -