An Automated Face Retrieval System Using Grasshopper Optimization Algorithm-Based Feature Selection Method

  • Arun Kumar ShuklaEmail author
  • Suvendu Kanungo
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 35)


Facial image retrieval using its contents is one of the major areas of research because of the exponential increase of multimedia data over the Internet. However, due to high dimensional features and different variations available in the images, it becomes a challenging task to obtain the relevant and non-redundant features. Therefore, for making the facial retrieval system more accurate and computationally efficient, the selection of prominent features is an important phase. In this paper, the grasshopper optimization algorithm has been used to obtain the relevant attributes from the high dimensional features vector. For the same, Oracle Research Laboratory database of faces is used. The experimental values show the efficacy of the proposed method of feature selection which eliminates the maximum 83% features among the other considered methods and the accuracy of the facial retrieval system also increases to 91.5%.


Face retrieval system Feature selection Clustering Grasshopper optimization algorithm 


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringBirla Institute of Technology, Mesra, RanchiAllahabadIndia

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