Application of Firefly Algorithm for Face Recognition

  • Jai Kotia
  • Rishika Bharti
  • Adit KotwalEmail author
  • Ramchandra Mangrulkar
Part of the Springer Tracts in Nature-Inspired Computing book series (STNIC)


Face Recognition is steadily making its way into commercial products. As such, the accuracy of Face Recognition systems is becoming extremely crucial. In the Firefly Algorithm, the brightness of fireflies is used to measure attraction between a pair of unisex fireflies. The firefly with higher brightness attracts the less bright firefly. The objective function is defined in proportion to the brightness, to define a maximization problem. This chapter aims to present the promising application of the Firefly Algorithm for Face Recognition. The Firefly Algorithm is used in a hyperdimensional feature space to select features that maximize the recognition accuracy. This chapter delineates how the Firefly Algorithm is a suitable algorithm for selection of the features in a Face Recognition model. The Firefly Algorithm is then applied to this feature space to identify and select the best features. Fireflies are arbitrarily placed on various focal points of the image under consideration. The advantage of this approach is its fast convergence in selecting the best features. The gamma parameter (\(\gamma \)) controls the movement of fireflies in this feature space and can be tuned for gaining an improvement in the performance of the Face Recognition model. This chapter aims to evaluate the performance and viability of using the Firefly Algorithm for Face Recognition.


Firefly Algorithm Face Recognition Feature extraction Machine learning Image processing 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Jai Kotia
    • 1
  • Rishika Bharti
    • 1
  • Adit Kotwal
    • 1
    Email author
  • Ramchandra Mangrulkar
    • 1
  1. 1.Dwarkadas J. Sanghvi College of EngineeringVile Parle, MumbaiIndia

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