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Fuzzy Enhancement for Efficient Emotion Detection from Facial Images

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Book cover Soft Computing for Problem Solving

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 816))

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Abstract

Human–computer interaction is one of the emerging fields facilitating computers to better understand human behavior. One such mode is through emotions displayed in facial images. Emotion detection requires real-time data acquisition. More often, the images are degraded due to poor illumination. Image enhancement becomes mandatory for precise emotion detection from facial images. Fuzzy logic works well for contrast enhancement as it deals with uncertainties in image acquisition well. A new methodology for contrast enhancement of facial images based on new improved fuzzy set theory is proposed. The proposed approach is carried out in three phases. Firstly, the overall brightness is adjusted using a trigonometric function to change the dynamic range of the image. Secondly, two different membership functions are established based on the histogram to adjust the local contrast of image details. The performance metrics like average information count (AIC) and natural image quality evaluator (NIQE) were used to evaluate the proposed method which generated on an average 89% decrease in NIQE value and 10% increase in AIC value.

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Authors and Affiliations

  1. Center for Automation and Robotics, Hindustan Institute of Technology and Science, Padur, Chennai, Tamil Nadu, India

    Payal Bhattacherjee & M. M. Ramya

Authors
  1. Payal Bhattacherjee
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  2. M. M. Ramya
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Corresponding author

Correspondence to Payal Bhattacherjee .

Editor information

Editors and Affiliations

  1. Department of Mathematics, South Asian University New Delhi , New Delhi, India

    Jagdish Chand Bansal

  2. Department of Mathematics, National Institute Of Technology Silchar Department of Mathematics, Silchar, Assam, India

    Kedar Nath Das

  3. Department of Mathematics and Computer Science, Faculty of Science, , Liverpool Hope University, Liverpool, UK

    Atulya Nagar

  4. Department of Mathematics, Indian Institute of Technology Roor Department of Mathematics, Roorkee, Uttarakhand, India

    Kusum Deep

  5. School of Basic Sciences, Indian Institute of Technology Bhubanesw School of Basic Sciences, Bhubaneswar, Odisha, India

    Akshay Kumar Ojha

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Bhattacherjee, P., Ramya, M.M. (2019). Fuzzy Enhancement for Efficient Emotion Detection from Facial Images. In: Bansal, J., Das, K., Nagar, A., Deep, K., Ojha, A. (eds) Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 816. Springer, Singapore. https://doi.org/10.1007/978-981-13-1592-3_5

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