A hybrid fuzzy-genetic colour classification system with best colour space selection under dynamically-changing illumination

Heesang Shin; Napoleon H. Reyes; Andre L. Barczak

doi:10.1007/978-3-642-17534-3_36

A hybrid fuzzy-genetic colour classification system with best colour space selection under dynamically-changing illumination

Heesang Shin^*, Napoleon H. Reyes, Andre L. Barczak

^*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

This paper contributes in colour classification under dynamically changing illumination, extending further the capabilities of our previous works on Fuzzy Colour Contrast Fusion (FCCF), FCCF-Heuristic Assisted Genetic Algorithm (HAGA) for automatic colour classifier calibration and Variable Colour Depth (VCD). All the aforementioned algorithms were proven to accurately in real-time with a pie-slice technique. However, the pie-slice classifier is the accuracy-limiting factor in these systems. Although it is possible to address this problem by using a more complex shape for specifying the colour decision region, this would only increase the chances of overfitting. We propose a hybrid colour classification system that automatically searches for the best colour space for classifying any target colour. Moreover, this paper also investigates the general selection of training sets to get a better understanding of the generalisation capability of FCCF-HAGA. The experiments used a professional Munsell ColorChecker Chart with extreme illumination conditions where the colour channels start hitting their dynamic range limits.

Original language	English
Title of host publication	Neural Information Processing. Models and Applications - 17th International Conference, ICONIP 2010, Proceedings
Editors	Kok Wai Wong, B. Sumudu Mendis, Abdesselam Bouzerdoum
Publisher	Springer
Pages	291-299
Number of pages	9
Volume	PART 2
ISBN (Print)	3642175333, 9783642175336
DOIs	https://doi.org/10.1007/978-3-642-17534-3_36
Publication status	Published - 2010
Externally published	Yes
Event	17th International Conference on Neural Information Processing, ICONIP 2010 - Sydney, NSW, Australia Duration: 22 Nov 2010 → 25 Nov 2010 Conference number: 17th

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	6444 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	17th International Conference on Neural Information Processing, ICONIP 2010
Abbreviated title	ICONIP 2010
Country/Territory	Australia
City	Sydney, NSW
Period	22/11/10 → 25/11/10

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10.1007/978-3-642-17534-3_36

Cite this

Shin, H., Reyes, N. H., & Barczak, A. L. (2010). A hybrid fuzzy-genetic colour classification system with best colour space selection under dynamically-changing illumination. In K. W. Wong, B. S. Mendis, & A. Bouzerdoum (Eds.), Neural Information Processing. Models and Applications - 17th International Conference, ICONIP 2010, Proceedings (Vol. PART 2, pp. 291-299). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6444 LNCS, No. PART 2). Springer. https://doi.org/10.1007/978-3-642-17534-3_36

Shin, Heesang ; Reyes, Napoleon H. ; Barczak, Andre L. / A hybrid fuzzy-genetic colour classification system with best colour space selection under dynamically-changing illumination. Neural Information Processing. Models and Applications - 17th International Conference, ICONIP 2010, Proceedings. editor / Kok Wai Wong ; B. Sumudu Mendis ; Abdesselam Bouzerdoum. Vol. PART 2 Springer, 2010. pp. 291-299 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

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title = "A hybrid fuzzy-genetic colour classification system with best colour space selection under dynamically-changing illumination",

abstract = "This paper contributes in colour classification under dynamically changing illumination, extending further the capabilities of our previous works on Fuzzy Colour Contrast Fusion (FCCF), FCCF-Heuristic Assisted Genetic Algorithm (HAGA) for automatic colour classifier calibration and Variable Colour Depth (VCD). All the aforementioned algorithms were proven to accurately in real-time with a pie-slice technique. However, the pie-slice classifier is the accuracy-limiting factor in these systems. Although it is possible to address this problem by using a more complex shape for specifying the colour decision region, this would only increase the chances of overfitting. We propose a hybrid colour classification system that automatically searches for the best colour space for classifying any target colour. Moreover, this paper also investigates the general selection of training sets to get a better understanding of the generalisation capability of FCCF-HAGA. The experiments used a professional Munsell ColorChecker Chart with extreme illumination conditions where the colour channels start hitting their dynamic range limits.",

author = "Heesang Shin and Reyes, {Napoleon H.} and Barczak, {Andre L.}",

year = "2010",

doi = "10.1007/978-3-642-17534-3_36",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Shin, H, Reyes, NH & Barczak, AL 2010, A hybrid fuzzy-genetic colour classification system with best colour space selection under dynamically-changing illumination. in KW Wong, BS Mendis & A Bouzerdoum (eds), Neural Information Processing. Models and Applications - 17th International Conference, ICONIP 2010, Proceedings. vol. PART 2, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 6444 LNCS, Springer, pp. 291-299, 17th International Conference on Neural Information Processing, ICONIP 2010, Sydney, NSW, New South Wales, Australia, 22/11/10. https://doi.org/10.1007/978-3-642-17534-3_36

A hybrid fuzzy-genetic colour classification system with best colour space selection under dynamically-changing illumination. / Shin, Heesang; Reyes, Napoleon H.; Barczak, Andre L.
Neural Information Processing. Models and Applications - 17th International Conference, ICONIP 2010, Proceedings. ed. / Kok Wai Wong; B. Sumudu Mendis; Abdesselam Bouzerdoum. Vol. PART 2 Springer, 2010. p. 291-299 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6444 LNCS, No. PART 2).

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

TY - GEN

T1 - A hybrid fuzzy-genetic colour classification system with best colour space selection under dynamically-changing illumination

AU - Shin, Heesang

AU - Reyes, Napoleon H.

AU - Barczak, Andre L.

N1 - Conference code: 17th

PY - 2010

Y1 - 2010

N2 - This paper contributes in colour classification under dynamically changing illumination, extending further the capabilities of our previous works on Fuzzy Colour Contrast Fusion (FCCF), FCCF-Heuristic Assisted Genetic Algorithm (HAGA) for automatic colour classifier calibration and Variable Colour Depth (VCD). All the aforementioned algorithms were proven to accurately in real-time with a pie-slice technique. However, the pie-slice classifier is the accuracy-limiting factor in these systems. Although it is possible to address this problem by using a more complex shape for specifying the colour decision region, this would only increase the chances of overfitting. We propose a hybrid colour classification system that automatically searches for the best colour space for classifying any target colour. Moreover, this paper also investigates the general selection of training sets to get a better understanding of the generalisation capability of FCCF-HAGA. The experiments used a professional Munsell ColorChecker Chart with extreme illumination conditions where the colour channels start hitting their dynamic range limits.

AB - This paper contributes in colour classification under dynamically changing illumination, extending further the capabilities of our previous works on Fuzzy Colour Contrast Fusion (FCCF), FCCF-Heuristic Assisted Genetic Algorithm (HAGA) for automatic colour classifier calibration and Variable Colour Depth (VCD). All the aforementioned algorithms were proven to accurately in real-time with a pie-slice technique. However, the pie-slice classifier is the accuracy-limiting factor in these systems. Although it is possible to address this problem by using a more complex shape for specifying the colour decision region, this would only increase the chances of overfitting. We propose a hybrid colour classification system that automatically searches for the best colour space for classifying any target colour. Moreover, this paper also investigates the general selection of training sets to get a better understanding of the generalisation capability of FCCF-HAGA. The experiments used a professional Munsell ColorChecker Chart with extreme illumination conditions where the colour channels start hitting their dynamic range limits.

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DO - 10.1007/978-3-642-17534-3_36

M3 - Conference contribution

AN - SCOPUS:78650192677

SN - 3642175333

SN - 9783642175336

VL - PART 2

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 291

EP - 299

BT - Neural Information Processing. Models and Applications - 17th International Conference, ICONIP 2010, Proceedings

A2 - Wong, Kok Wai

A2 - Mendis, B. Sumudu

A2 - Bouzerdoum, Abdesselam

PB - Springer

T2 - 17th International Conference on Neural Information Processing, ICONIP 2010

Y2 - 22 November 2010 through 25 November 2010

ER -

Shin H, Reyes NH, Barczak AL. A hybrid fuzzy-genetic colour classification system with best colour space selection under dynamically-changing illumination. In Wong KW, Mendis BS, Bouzerdoum A, editors, Neural Information Processing. Models and Applications - 17th International Conference, ICONIP 2010, Proceedings. Vol. PART 2. Springer. 2010. p. 291-299. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-17534-3_36

A hybrid fuzzy-genetic colour classification system with best colour space selection under dynamically-changing illumination

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