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A Neuro-Fuzzy Approach for Compensating Color Backlight Images

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Abstract

This paper presents a neuro-fuzzy approach for compensating exposure in the case of backlighting, regardless of the position of objects. To achieve the compensation effect, the fuzzy C-means algorithm is first used to extract features from a backlight image. Then these extracted features are presented to a trained artificial immune system based neuro-fuzzy system (AISNFS) to estimate the amount of compensation. Finally, the estimated amount of compensation incorporated with a compensation equation is used to enhance the intensity component of the backlight image to produce a compensated image. Several backlight images were used to test the performance of the algorithm.

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Authors and Affiliations

  1. Department of Computer Science & Information Engineering, National Central University, Taiwan, R.O.C

    Mu-Chun Su, Yuan-Shao Yang, Jonathan Lee & Gwo-Dong Chen

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  1. Mu-Chun Su
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  2. Yuan-Shao Yang
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  3. Jonathan Lee
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  4. Gwo-Dong Chen
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Correspondence to Mu-Chun Su.

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Su, MC., Yang, YS., Lee, J. et al. A Neuro-Fuzzy Approach for Compensating Color Backlight Images. Neural Process Lett 23, 273–287 (2006). https://doi.org/10.1007/s11063-006-9002-0

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  • DOI: https://doi.org/10.1007/s11063-006-9002-0

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