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Heuristic Approach for Face Recognition using Artificial Bee Colony Optimization

  • Astha Gupta
  • Lavika Goel
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 530)

Abstract

Artificial Bee Colony (ABC) algorithm is inspired by the intelligent behavior of the bees to optimize their search for food resources. It is a lately developed algorithm in Swarm Intelligence (SI) that outperforms many of the established and widely used algorithms like Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) under SI. ABC is being applied in diverse areas to improve performance. Many hybrids of ABC have evolved over the years to overcome its weaknesses and better suit applications. In this paper ABC is being applied to the field of Face Recognition, which remains largely unexplored in context of ABC algorithm. The paper describes the challenges and methodology used to adapt ABC to Face Recognition. In this paper, features are extracted by first applying Gabor Filter. On the features obtained, PCA (Principal Component Analysis) is applied to reduce their dimensionality. A modified version of ABC is then used on the feature vectors to search for best match to test image in the given database.

Keywords

Particle Swarm Optimization Face Recognition Swarm Intelligence Gabor Filter Face Recognition System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Information SystemsBITS PilaniPilaniIndia

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