Robust light objects recognition based on computer vision

Yi Yuan Chen; Kuen Ming Lan; Hung I. Pai; Jen-Hui Chuang; Chii Yah Yuan

doi:10.1109/I-SPAN.2009.16

Robust light objects recognition based on computer vision

Yi Yuan Chen^*, Kuen Ming Lan, Hung I. Pai, Jen-Hui Chuang, Chii Yah Yuan

^*Corresponding author for this work

Department of Computer Science

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

3 Scopus citations

Abstract

This paper proposes a recognition method for light objects in a video for real-time application and the movement of the surrounding objects. The method extracts the objects by considering known geometric arrangements and blinking frequency, while the latter is also used to remove the image noise. Therefore, locations of the light objects can be found rapidly, and the on-off blinking states of these objects can be recognized accordingly if the frame rate of the video is sufficient. Besides, it can be used in the image recognition unit of a light communication system.

Original language	English
Title of host publication	I-SPAN 2009 - The 10th International Symposium on Pervasive Systems, Algorithms, and Networks
Pages	508-514
Number of pages	7
DOIs	https://doi.org/10.1109/I-SPAN.2009.16
State	Published - 1 Dec 2009
Event	10th International Symposium on Pervasive Systems, Algorithms, and Networks, I-SPAN 2009 - Kaohsiung, Taiwan Duration: 14 Dec 2009 → 16 Dec 2009

Publication series

Name	I-SPAN 2009 - The 10th International Symposium on Pervasive Systems, Algorithms, and Networks

Conference

Conference	10th International Symposium on Pervasive Systems, Algorithms, and Networks, I-SPAN 2009
Country	Taiwan
City	Kaohsiung
Period	14/12/09 → 16/12/09

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10.1109/I-SPAN.2009.16

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Chen, Y. Y., Lan, K. M., Pai, H. I., Chuang, J-H., & Yuan, C. Y. (2009). Robust light objects recognition based on computer vision. In I-SPAN 2009 - The 10th International Symposium on Pervasive Systems, Algorithms, and Networks (pp. 508-514). [5381601] (I-SPAN 2009 - The 10th International Symposium on Pervasive Systems, Algorithms, and Networks). https://doi.org/10.1109/I-SPAN.2009.16

@inproceedings{288db096add44cfcaa85a90d0a1c658a,

title = "Robust light objects recognition based on computer vision",

abstract = "This paper proposes a recognition method for light objects in a video for real-time application and the movement of the surrounding objects. The method extracts the objects by considering known geometric arrangements and blinking frequency, while the latter is also used to remove the image noise. Therefore, locations of the light objects can be found rapidly, and the on-off blinking states of these objects can be recognized accordingly if the frame rate of the video is sufficient. Besides, it can be used in the image recognition unit of a light communication system.",

author = "Chen, {Yi Yuan} and Lan, {Kuen Ming} and Pai, {Hung I.} and Jen-Hui Chuang and Yuan, {Chii Yah}",

year = "2009",

month = dec,

day = "1",

doi = "10.1109/I-SPAN.2009.16",

language = "English",

isbn = "9780769539089",

series = "I-SPAN 2009 - The 10th International Symposium on Pervasive Systems, Algorithms, and Networks",

pages = "508--514",

booktitle = "I-SPAN 2009 - The 10th International Symposium on Pervasive Systems, Algorithms, and Networks",

note = "null ; Conference date: 14-12-2009 Through 16-12-2009",

}

Chen, YY, Lan, KM, Pai, HI, Chuang, J-H & Yuan, CY 2009, Robust light objects recognition based on computer vision. in I-SPAN 2009 - The 10th International Symposium on Pervasive Systems, Algorithms, and Networks., 5381601, I-SPAN 2009 - The 10th International Symposium on Pervasive Systems, Algorithms, and Networks, pp. 508-514, 10th International Symposium on Pervasive Systems, Algorithms, and Networks, I-SPAN 2009, Kaohsiung, Taiwan, 14/12/09. https://doi.org/10.1109/I-SPAN.2009.16

Robust light objects recognition based on computer vision. / Chen, Yi Yuan; Lan, Kuen Ming; Pai, Hung I.; Chuang, Jen-Hui; Yuan, Chii Yah.

I-SPAN 2009 - The 10th International Symposium on Pervasive Systems, Algorithms, and Networks. 2009. p. 508-514 5381601 (I-SPAN 2009 - The 10th International Symposium on Pervasive Systems, Algorithms, and Networks).

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

TY - GEN

T1 - Robust light objects recognition based on computer vision

AU - Chen, Yi Yuan

AU - Lan, Kuen Ming

AU - Pai, Hung I.

AU - Chuang, Jen-Hui

AU - Yuan, Chii Yah

PY - 2009/12/1

Y1 - 2009/12/1

N2 - This paper proposes a recognition method for light objects in a video for real-time application and the movement of the surrounding objects. The method extracts the objects by considering known geometric arrangements and blinking frequency, while the latter is also used to remove the image noise. Therefore, locations of the light objects can be found rapidly, and the on-off blinking states of these objects can be recognized accordingly if the frame rate of the video is sufficient. Besides, it can be used in the image recognition unit of a light communication system.

AB - This paper proposes a recognition method for light objects in a video for real-time application and the movement of the surrounding objects. The method extracts the objects by considering known geometric arrangements and blinking frequency, while the latter is also used to remove the image noise. Therefore, locations of the light objects can be found rapidly, and the on-off blinking states of these objects can be recognized accordingly if the frame rate of the video is sufficient. Besides, it can be used in the image recognition unit of a light communication system.

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U2 - 10.1109/I-SPAN.2009.16

DO - 10.1109/I-SPAN.2009.16

M3 - Conference contribution

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SN - 9780769539089

T3 - I-SPAN 2009 - The 10th International Symposium on Pervasive Systems, Algorithms, and Networks

SP - 508

EP - 514

BT - I-SPAN 2009 - The 10th International Symposium on Pervasive Systems, Algorithms, and Networks

Y2 - 14 December 2009 through 16 December 2009

ER -

Robust light objects recognition based on computer vision

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