The use of visible color difference in the quantitative evaluation of color image segmentation

Hsin Chia Chen; Sheng-Jyh Wang

doi:10.1109/ICASSP.2004.1326614

The use of visible color difference in the quantitative evaluation of color image segmentation

Hsin Chia Chen^*, Sheng-Jyh Wang

^*Corresponding author for this work

Department of Electronics Engineering

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

30 Scopus citations

Abstract

In this paper, we propose the use of visible color difference in a new quantitative evaluation scheme for color image segmentation. With visible color difference, two measurements, named intra-region visual error and inter-region visual error, are defined to evaluate the quality of segmentation results. To fit for human's visual perception, segmentation results with an excessive amount of intra-region error are regarded as under-segmeritation, while segmentation results with too many inter-region errors are regarded as over-segmentation. Based on these two measurements, a complete scheme for the evaluation of color image segmentation is proposed. The simulation results demonstrate that this new scheme may provide a reliable and efficient way to automatically select the parameter settings for a given segmentation algorithm and to compare the performance between various segmentation algorithms.

Original language	English
Journal	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	3
DOIs	https://doi.org/10.1109/ICASSP.2004.1326614
State	Published - 28 Sep 2004
Event	Proceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing - Montreal, Que, Canada Duration: 17 May 2004 → 21 May 2004

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abstract = "In this paper, we propose the use of visible color difference in a new quantitative evaluation scheme for color image segmentation. With visible color difference, two measurements, named intra-region visual error and inter-region visual error, are defined to evaluate the quality of segmentation results. To fit for human's visual perception, segmentation results with an excessive amount of intra-region error are regarded as under-segmeritation, while segmentation results with too many inter-region errors are regarded as over-segmentation. Based on these two measurements, a complete scheme for the evaluation of color image segmentation is proposed. The simulation results demonstrate that this new scheme may provide a reliable and efficient way to automatically select the parameter settings for a given segmentation algorithm and to compare the performance between various segmentation algorithms.",

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