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Marker Controlled Watershed Segmented Features Based Facial Expression Recognition Using Neuro-Fuzzy Architecture

In: New Trends in Computational Vision and Bio-inspired Computing

Author

Listed:
  • K. Sujatha

    (Dr. MGR Educational and Research Institute, Department of EEE)

  • V. Balaji

    (JNN Institute of Engineering, Department of EEE)

  • P. Vijaibabu

    (Dr. MGR Educational and Research Institute, Department of EEE)

  • V. Karthikeyan

    (Dr. MGR Educational and Research Institute, Department of EEE)

  • N. P. G. Bhavani

    (Meenakshi College of Engineering, Department of EEE)

  • V. Srividhya

    (Meenakshi College of Engineering, Department of EEE)

  • P. SaiKrishna

    (Dr. MGR Educational and Research Institute, Department of ECE)

  • A. Kannan

    (Dr. MGR Educational and Research Institute
    Meenakshi College of Engineering)

  • N. Jayachitra

    (Dr. MGR Educational and Research Institute, Department of Chemical Engineering)

  • Safia

    (Dr. MGR Educational and Research Institute, Department of ECE)

Abstract

Facial Expression gives significant information about emotion of a person. In this investigation area of machine vision, automated facial expression recognition is an important area because of its significance in Human Computer Interaction (HCI). To improve the state of interaction in man machine communication systems, extraction and validation of emotional information by facial expression analysis plays a major role. The proposed method in facial expression identification is dependent on Marker Controlled Watershed segmentation for Features. The granulometry of the image and the first derivative were used as texture features. The artificial intelligent system called Adaptive Neuro-Fuzzy Inference System (ANFIS) is used for finding the facial expressions. The performance of the proposed methodology is validated which yield promising performance showing the effectiveness of the recognition system.

Suggested Citation

  • K. Sujatha & V. Balaji & P. Vijaibabu & V. Karthikeyan & N. P. G. Bhavani & V. Srividhya & P. SaiKrishna & A. Kannan & N. Jayachitra & Safia, 2020. "Marker Controlled Watershed Segmented Features Based Facial Expression Recognition Using Neuro-Fuzzy Architecture," Springer Books, in: S. Smys & Abdullah M. Iliyasu & Robert Bestak & Fuqian Shi (ed.), New Trends in Computational Vision and Bio-inspired Computing, pages 1333-1341, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-41862-5_136
    DOI: 10.1007/978-3-030-41862-5_136
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