Symbolic pixel labeling for curvilinear feature detection

John Canning; J. John Kim; Nathan Netanyahu; Azriel Rosenfeld

doi:10.1016/0167-8655(88)90079-7

Symbolic pixel labeling for curvilinear feature detection

John Canning, J. John Kim, Nathan Netanyahu, Azriel Rosenfeld

University of Maryland, College Park

Research output: Contribution to journal › Article › peer-review

10 Scopus citations

Abstract

This paper describes a method of detecting thin curvilinear features in an image based on a detailed analysis of the local gray level patterns at each pixel. This allows operations such as thinning and gap filling to be based on more accurate information.

Original language	English
Pages (from-to)	299-310
Number of pages	12
Journal	Pattern Recognition Letters
Volume	8
Issue number	5
DOIs	https://doi.org/10.1016/0167-8655(88)90079-7
State	Published - Dec 1988
Externally published	Yes

Bibliographical note

Funding Information:
The support of the Defense Mapping Agency under Contract DMA 85 C 0007 is gratefully acknowledged, as is the help of Sandy German in preparing this paper.

Funding

The support of the Defense Mapping Agency under Contract DMA 85 C 0007 is gratefully acknowledged, as is the help of Sandy German in preparing this paper.

Funders	Funder number
Defense Mapping Agency	DMA 85 C 0007

Keywords

curve detection
line detection
pixel labeling

Access to Document

10.1016/0167-8655(88)90079-7

Cite this

@article{5b63fa46d2f24a29a4e3dfcca7a76dd9,

title = "Symbolic pixel labeling for curvilinear feature detection",

abstract = "This paper describes a method of detecting thin curvilinear features in an image based on a detailed analysis of the local gray level patterns at each pixel. This allows operations such as thinning and gap filling to be based on more accurate information.",

keywords = "curve detection, line detection, pixel labeling",

author = "John Canning and Kim, {J. John} and Nathan Netanyahu and Azriel Rosenfeld",

note = "Funding Information: The support of the Defense Mapping Agency under Contract DMA 85 C 0007 is gratefully acknowledged, as is the help of Sandy German in preparing this paper.",

year = "1988",

month = dec,

doi = "10.1016/0167-8655(88)90079-7",

language = "אנגלית",

volume = "8",

pages = "299--310",

journal = "Pattern Recognition Letters",

issn = "0167-8655",

publisher = "Elsevier",

number = "5",

}

TY - JOUR

T1 - Symbolic pixel labeling for curvilinear feature detection

AU - Canning, John

AU - Kim, J. John

AU - Netanyahu, Nathan

AU - Rosenfeld, Azriel

N1 - Funding Information: The support of the Defense Mapping Agency under Contract DMA 85 C 0007 is gratefully acknowledged, as is the help of Sandy German in preparing this paper.

PY - 1988/12

Y1 - 1988/12

N2 - This paper describes a method of detecting thin curvilinear features in an image based on a detailed analysis of the local gray level patterns at each pixel. This allows operations such as thinning and gap filling to be based on more accurate information.

AB - This paper describes a method of detecting thin curvilinear features in an image based on a detailed analysis of the local gray level patterns at each pixel. This allows operations such as thinning and gap filling to be based on more accurate information.

KW - curve detection

KW - line detection

KW - pixel labeling

UR - http://www.scopus.com/inward/record.url?scp=0024200195&partnerID=8YFLogxK

U2 - 10.1016/0167-8655(88)90079-7

DO - 10.1016/0167-8655(88)90079-7

M3 - ???researchoutput.researchoutputtypes.contributiontojournal.article???

AN - SCOPUS:0024200195

SN - 0167-8655

VL - 8

SP - 299

EP - 310

JO - Pattern Recognition Letters

JF - Pattern Recognition Letters

IS - 5

ER -

Symbolic pixel labeling for curvilinear feature detection

Abstract

Bibliographical note

Funding

Keywords

Access to Document

Other files and links

Fingerprint

Cite this