An Image Processing and Analysis Systems for Automatic Classification of Cigarette Filter Blockage

J. P. Stitt; R. J. O'Connor; L. T. Kozlowski

An Image Processing and Analysis Systems for Automatic Classification of Cigarette Filter Blockage

J. P. Stitt
, R. J. O'Connor
, L. T. Kozlowski

Community Health and Health Behavior CHHB

University at Buffalo

Pennsylvania State University

Research output: Contribution to journal › Conference article › peer-review

5 Scopus citations

Abstract

Most filter cigarettes today employ ventilated filters. Heavily ventilated filters have been found to be "elastic" in that they contribute to lower tar numbers in standard smoking-machine tests while at the same time allowing smokers to get much higher doses of tar from the same cigarette when they block vents with fingers or lips. This paper describes a method for automating a Stain Pattern technique which permits unobtrusive measurement of behavioral vent blocking. This automation could provide a more accurate analysis of filter efficacy. The system employs image processing and analysis to generate a set of unbiased features which are subsequently categorized by a fuzzy set based classifier.

Original language	English
Pages (from-to)	926-929
Number of pages	4
Journal	Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume	1
State	Published - 2003
Event	A New Beginning for Human Health: Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Cancun, Mexico Duration: Sep 17 2003 → Sep 21 2003

Keywords

Cigarette Smoking
Image Analysis
Pattern Recognition

Cite this

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title = "An Image Processing and Analysis Systems for Automatic Classification of Cigarette Filter Blockage",

abstract = "Most filter cigarettes today employ ventilated filters. Heavily ventilated filters have been found to be {"}elastic{"} in that they contribute to lower tar numbers in standard smoking-machine tests while at the same time allowing smokers to get much higher doses of tar from the same cigarette when they block vents with fingers or lips. This paper describes a method for automating a Stain Pattern technique which permits unobtrusive measurement of behavioral vent blocking. This automation could provide a more accurate analysis of filter efficacy. The system employs image processing and analysis to generate a set of unbiased features which are subsequently categorized by a fuzzy set based classifier.",

keywords = "Cigarette Smoking, Image Analysis, Pattern Recognition",

author = "Stitt, \{J. P.\} and O'Connor, \{R. J.\} and Kozlowski, \{L. T.\}",

year = "2003",

language = "English",

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journal = "Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings",

issn = "0589-1019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "A New Beginning for Human Health: Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society ; Conference date: 17-09-2003 Through 21-09-2003",

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TY - JOUR

T1 - An Image Processing and Analysis Systems for Automatic Classification of Cigarette Filter Blockage

AU - Stitt, J. P.

AU - O'Connor, R. J.

AU - Kozlowski, L. T.

PY - 2003

Y1 - 2003

N2 - Most filter cigarettes today employ ventilated filters. Heavily ventilated filters have been found to be "elastic" in that they contribute to lower tar numbers in standard smoking-machine tests while at the same time allowing smokers to get much higher doses of tar from the same cigarette when they block vents with fingers or lips. This paper describes a method for automating a Stain Pattern technique which permits unobtrusive measurement of behavioral vent blocking. This automation could provide a more accurate analysis of filter efficacy. The system employs image processing and analysis to generate a set of unbiased features which are subsequently categorized by a fuzzy set based classifier.

AB - Most filter cigarettes today employ ventilated filters. Heavily ventilated filters have been found to be "elastic" in that they contribute to lower tar numbers in standard smoking-machine tests while at the same time allowing smokers to get much higher doses of tar from the same cigarette when they block vents with fingers or lips. This paper describes a method for automating a Stain Pattern technique which permits unobtrusive measurement of behavioral vent blocking. This automation could provide a more accurate analysis of filter efficacy. The system employs image processing and analysis to generate a set of unbiased features which are subsequently categorized by a fuzzy set based classifier.

KW - Cigarette Smoking

KW - Image Analysis

KW - Pattern Recognition

UR - https://www.scopus.com/pages/publications/1542332444

M3 - Conference article

SN - 0589-1019

VL - 1

SP - 926

EP - 929

JO - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

JF - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

T2 - A New Beginning for Human Health: Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Y2 - 17 September 2003 through 21 September 2003

ER -

An Image Processing and Analysis Systems for Automatic Classification of Cigarette Filter Blockage

Abstract

Keywords

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