A novel probabilistic appearance model for cigarette detection under illumination change

Han Wang; Daviad K. Han; Quan Shi; Hanseok Ko

doi:10.23919/ELINFOCOM.2019.8706404

A novel probabilistic appearance model for cigarette detection under illumination change

Han Wang, Daviad K. Han, Quan Shi, Hanseok Ko

School of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

An effective appearance model is proposed for detecting cigarettes individually in a tightly packed bundle based on an intensity variance probabilistic model. Conventional image intensity threshold based segmentation is brittle and susceptible to environmental variation such as an illumination change. To mitigate this problem, a geometrical snow model is designed to describe the image intensity variances of an individual cigarette. It is then combined with a Gaussian function to generate a probabilistic model of a cigarette detector. The experimental results show that the proposed appearance model provides accurate detection performances and that it is robust to illumination change compared with other conventional methods.

Original language	English
Title of host publication	ICEIC 2019 - International Conference on Electronics, Information, and Communication
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9788995004449
DOIs	https://doi.org/10.23919/ELINFOCOM.2019.8706404
Publication status	Published - 2019 May 3
Event	18th International Conference on Electronics, Information, and Communication, ICEIC 2019 - Auckland, New Zealand Duration: 2019 Jan 22 → 2019 Jan 25

Publication series

Name	ICEIC 2019 - International Conference on Electronics, Information, and Communication

Conference

Conference	18th International Conference on Electronics, Information, and Communication, ICEIC 2019
Country/Territory	New Zealand
City	Auckland
Period	19/1/22 → 19/1/25

Bibliographical note

Funding Information:
This work was supported in part by the National Natural Science Foundation of China (61872425, 61771265 and 61801247), in part by the University Science Research of Jiangsu Province Foundation(17KJB520029), the "333" Talents of Jiangsu(BRA2017475) ,the Qing LAN project of Jiangsu, the Science and technology Project of Nantong(CP2017001, GY12017006),in part by Nantong University (17R31), and in part by the Basic Science Research Program of NRF (NRF-2017R1A2B4012720)..

Publisher Copyright:
© 2019 Institute of Electronics and Information Engineers (IEIE).

Keywords

Appearance model
Cigarette detection
Illumination change

ASJC Scopus subject areas

Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.23919/ELINFOCOM.2019.8706404

Cite this

Wang, H., Han, D. K., Shi, Q., & Ko, H. (2019). A novel probabilistic appearance model for cigarette detection under illumination change. In ICEIC 2019 - International Conference on Electronics, Information, and Communication Article 8706404 (ICEIC 2019 - International Conference on Electronics, Information, and Communication). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ELINFOCOM.2019.8706404

A novel probabilistic appearance model for cigarette detection under illumination change. / Wang, Han; Han, Daviad K.; Shi, Quan et al.
ICEIC 2019 - International Conference on Electronics, Information, and Communication. Institute of Electrical and Electronics Engineers Inc., 2019. 8706404 (ICEIC 2019 - International Conference on Electronics, Information, and Communication).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Wang, H, Han, DK, Shi, Q & Ko, H 2019, A novel probabilistic appearance model for cigarette detection under illumination change. in ICEIC 2019 - International Conference on Electronics, Information, and Communication., 8706404, ICEIC 2019 - International Conference on Electronics, Information, and Communication, Institute of Electrical and Electronics Engineers Inc., 18th International Conference on Electronics, Information, and Communication, ICEIC 2019, Auckland, New Zealand, 19/1/22. https://doi.org/10.23919/ELINFOCOM.2019.8706404

Wang H, Han DK, Shi Q, Ko H. A novel probabilistic appearance model for cigarette detection under illumination change. In ICEIC 2019 - International Conference on Electronics, Information, and Communication. Institute of Electrical and Electronics Engineers Inc. 2019. 8706404. (ICEIC 2019 - International Conference on Electronics, Information, and Communication). doi: 10.23919/ELINFOCOM.2019.8706404

Wang, Han ; Han, Daviad K. ; Shi, Quan et al. / A novel probabilistic appearance model for cigarette detection under illumination change. ICEIC 2019 - International Conference on Electronics, Information, and Communication. Institute of Electrical and Electronics Engineers Inc., 2019. (ICEIC 2019 - International Conference on Electronics, Information, and Communication).

@inproceedings{6cfd6c0da7cd42b5887417c050b705ce,

title = "A novel probabilistic appearance model for cigarette detection under illumination change",

abstract = "An effective appearance model is proposed for detecting cigarettes individually in a tightly packed bundle based on an intensity variance probabilistic model. Conventional image intensity threshold based segmentation is brittle and susceptible to environmental variation such as an illumination change. To mitigate this problem, a geometrical snow model is designed to describe the image intensity variances of an individual cigarette. It is then combined with a Gaussian function to generate a probabilistic model of a cigarette detector. The experimental results show that the proposed appearance model provides accurate detection performances and that it is robust to illumination change compared with other conventional methods.",

keywords = "Appearance model, Cigarette detection, Illumination change",

author = "Han Wang and Han, {Daviad K.} and Quan Shi and Hanseok Ko",

note = "Funding Information: This work was supported in part by the National Natural Science Foundation of China (61872425, 61771265 and 61801247), in part by the University Science Research of Jiangsu Province Foundation(17KJB520029), the {"}333{"} Talents of Jiangsu(BRA2017475) ,the Qing LAN project of Jiangsu, the Science and technology Project of Nantong(CP2017001, GY12017006),in part by Nantong University (17R31), and in part by the Basic Science Research Program of NRF (NRF-2017R1A2B4012720).. Publisher Copyright: {\textcopyright} 2019 Institute of Electronics and Information Engineers (IEIE).; 18th International Conference on Electronics, Information, and Communication, ICEIC 2019 ; Conference date: 22-01-2019 Through 25-01-2019",

year = "2019",

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doi = "10.23919/ELINFOCOM.2019.8706404",

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AU - Shi, Quan

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N1 - Funding Information: This work was supported in part by the National Natural Science Foundation of China (61872425, 61771265 and 61801247), in part by the University Science Research of Jiangsu Province Foundation(17KJB520029), the "333" Talents of Jiangsu(BRA2017475) ,the Qing LAN project of Jiangsu, the Science and technology Project of Nantong(CP2017001, GY12017006),in part by Nantong University (17R31), and in part by the Basic Science Research Program of NRF (NRF-2017R1A2B4012720).. Publisher Copyright: © 2019 Institute of Electronics and Information Engineers (IEIE).

PY - 2019/5/3

Y1 - 2019/5/3

N2 - An effective appearance model is proposed for detecting cigarettes individually in a tightly packed bundle based on an intensity variance probabilistic model. Conventional image intensity threshold based segmentation is brittle and susceptible to environmental variation such as an illumination change. To mitigate this problem, a geometrical snow model is designed to describe the image intensity variances of an individual cigarette. It is then combined with a Gaussian function to generate a probabilistic model of a cigarette detector. The experimental results show that the proposed appearance model provides accurate detection performances and that it is robust to illumination change compared with other conventional methods.

AB - An effective appearance model is proposed for detecting cigarettes individually in a tightly packed bundle based on an intensity variance probabilistic model. Conventional image intensity threshold based segmentation is brittle and susceptible to environmental variation such as an illumination change. To mitigate this problem, a geometrical snow model is designed to describe the image intensity variances of an individual cigarette. It is then combined with a Gaussian function to generate a probabilistic model of a cigarette detector. The experimental results show that the proposed appearance model provides accurate detection performances and that it is robust to illumination change compared with other conventional methods.

KW - Appearance model

KW - Cigarette detection

KW - Illumination change

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AN - SCOPUS:85065882210

T3 - ICEIC 2019 - International Conference on Electronics, Information, and Communication

BT - ICEIC 2019 - International Conference on Electronics, Information, and Communication

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 18th International Conference on Electronics, Information, and Communication, ICEIC 2019

Y2 - 22 January 2019 through 25 January 2019

ER -

A novel probabilistic appearance model for cigarette detection under illumination change

Abstract

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Bibliographical note

Keywords

ASJC Scopus subject areas

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