Earticle

초록

영어

Harmony search algorithm (HSA) is an evolutionary algorithm which is used to solve a wide class of problems. HSA is based on the idea of musician's behavior in searching for better harmonies. It tries to find the optimal solution according to an objective function. HSA has been applied to various optimization problems such as timetabling, text summarization, flood model calibration. In this paper we used HSA to select an optimal subset of features that gives a better accuracy results in solving the face recognition problem. The proposed approach is compared with the standard Principal Component Analysis (PCA). A set of images that each has a face adopted from the literature is used to evaluate the proposed algorithm. The obtained results show that using HSA to select the subset of features gives better accuracy in face recognition.

목차

Abstract
 1. Introduction
 2. Background
  2.1. Face Detection and Recognition
  2.2. Face Recognition using Evolutionary Algorithms
 3. Harmony Search Algorithm
 4. Methodology
  4.1. Principle Component Analysis (PCA)
  4.2. Harmony Based Face Recognition System
  4.3. Harmony Representation
  4.4. Euclidean Distance
  4.5. Cosine Similarity
 5. Evaluation and Results
  5.1. Introduction
  5.2. Experimental Results
 6. Conclusion and Future Work
 References

키워드

저자

• Rana Sawalha [ Faculty of Information Technology and Computer Science Yarmouk University ]
• Iyad Abu Doush [ Faculty of Information Technology and Computer Science Yarmouk University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605