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Reseach Article

An Image Searching Framework using Hybrid Algorithm

by Bello B. O., Iwayemi A.
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 178 - Number 21
Year of Publication: 2019
Authors: Bello B. O., Iwayemi A.
10.5120/ijca2019918976

Bello B. O., Iwayemi A. . An Image Searching Framework using Hybrid Algorithm. International Journal of Computer Applications. 178, 21 ( Jun 2019), 4-9. DOI=10.5120/ijca2019918976

@article{ 10.5120/ijca2019918976,
author = { Bello B. O., Iwayemi A. },
title = { An Image Searching Framework using Hybrid Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2019 },
volume = { 178 },
number = { 21 },
month = { Jun },
year = { 2019 },
issn = { 0975-8887 },
pages = { 4-9 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume178/number21/30656-2019918976/ },
doi = { 10.5120/ijca2019918976 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:51:01.315954+05:30
%A Bello B. O.
%A Iwayemi A.
%T An Image Searching Framework using Hybrid Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 178
%N 21
%P 4-9
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Searching the internet, World Wide Web or databases are only possible with textual index. In other words, images could only be retrieve by having searching parameter(s) that are in textual form. Also, text information is only retrievable by providing a textual search index. No matter how real or identical an image is to the real object, searching cannot be done through it. There will be need for a provision of a matching information in textual form if searching will be successful. This paper presents an image searching framework using facial recognition. The framework uses the hybrid of Genetic algorithm (GA) and Speed Up Robust Features (SURF) algorithm to locate face boundaries, extract facial features and interest points for recognition so as to retrieve a perfect match of image queried from the database. The whole process includes: the query interface, where user will be able to upload image for query and the next is detecting and extracting the facial features, the next step is to search the database for the best face matches.

References
  1. Dipalee, N. and Sandeep, U. 2014. Survey on Methodologies Used for Web Image Search, International Journal of Computer Applications, Vol. 107, No. 18.
  2. Lixin, D., Wen, L., Ivor, W., and Dong, X. 2011. Improving Web Image Search by Bag-Based Re-ranking, IEEE Transactions On Image Processing, Vol. 20, No. 11.
  3. Jugal, K., Maria A. and Xiaobo, Z. 2005. Implementation of an Image Search Engine, M.S. Project Report Computer Science Dept. p. 4.
  4. Vijayarani and Vinupriya 2014. Facial Image Classification and Searching –A Survey, International Journal of Information Technology, Modelling and Computing, Vol. 2, No. 2.
  5. Unmesh, M. and Samir, K. 2016. Face matching using SURF feature points, International Journal of Research in Advanced Engineering and Technology, Vol. 2, No. 1, pp. 16-18.
  6. Eugene, B. and Szil´ard, V. 2016. FaceMatch: real-world face image retrieval, U.S. National Library of Medicine Lister Hill National Center for Biomedical Communications, Vol. 709, pp. 405-419.
  7. Mayuri, D., Joshi, R., Deshmukh, M., Kalashree, N., Hemke, Ashwini, B. and Rakhi, W. 2014. Image Retrieval and Re-Ranking Techniques – A Survey, International Journal (SIPIJ), Vol. 5, No. 2, pp. 1-14.
  8. Avinash, N. and Meshram, B. 2013. Content Based Image Indexing and Retrieval, International Journal of Graphics and Image Processing, Vol. 3, No. 4, pp. 235-246.
  9. Tanmoy, M., Anupam, N., Ashok, D. and Muktinath, B. 2010. An Approach of Face Detection using Geometrical Definition of Human Face, National Conference on Computational Instrumentation CSIO, Chandigarh, India, pp. 97-99.
  10. Stylianos, A., Nikos, N. and Ioannis, P. 2008. Facial Feature Detection using Distance Vector Fields, Department of Informatics, Vol. 42, No. 7, pp. 1388-1398.
  11. Yong-Hawan, L., Bonam, K. and Heung-Jun, K. 2012. Indexing and Retrieving Photographic Image Using a Combination of Geo-Location and Content Based Features, Computing and Informatics, Vol. 30, No. 6, pp. 1115-1129.
  12. Vladimir, V., Stanislav, S. and Anna, D. 2007. Automatic Extraction of Frontal Facial Features, Dept. of Computational Mathematics and Cybernetics, Moscow State University.
  13. Paola, C., Raffaella, L. and Giuseppe, L. 2007. Automatic Facial Feature Extraction for Face Recognition, University degli Studi di Milano Italy, pp. 3-58.
  14. Zhengxi, W., Pan, Z. and Liren, Z. 2014. Design and implementation of image search algorithm. America Journal of Software Engineering and Applications’, Vol. 3, No. 6, pp. 90-94.
  15. Paul, V. and Michael, J. 2001. Rapid Object Detection using a Boosted Cascade of Simple Features, Institute of Electrical, Electronic Engineering, pp. 1-9.
  16. Oliver, J., Klaus, J. and Robert, W. 2001 Robust Face Detection Using the Hausdorff Distance, Biometric Person Authentication, Springer, Lecture Notes in Computer Science, Halmstad, Sweden, 2091, pp. 90–95.
  17. Geng, D., Fei, S. and Anni, C. 2016. Face Recognition using SURF Features, Pattern Recognition and Computer Vision.
  18. Wang, J., Tan, T. 2000. A New Face Detection Method Based on Shape Information, Pattern Recognition. Lett. 21: pp. 463-471.
  19. Saifuddin, M., Rubayat, P., Liton, J., Al-Almin, B. 2007. Robust Face Detection using Genetic Algorithm, Information Technology Journal, Vol. 6, No. 1.
  20. Yuille, A., Hallinan, P. and Cohen 1989. Feature Extraction from Face using Deformable Templates, International Journal of Computer Vission, Vol. 8.
  21. Bilgin, E., Bulent, S. and Emin, A. 1996. Facial Feature Extraction using Genetic Algorithms, Bogazici University Electrical Engineering Department, Bebek, 80815, Istanbul.
Index Terms

Computer Science
Information Sciences

Keywords

Genetic Algorithm SURF Face detection Face Extraction Query Pre-processing Recognition Extraction Localization Matching.