Image Similarity Test Using Eigenface Calculation

Authors

  • Nadya Andhika Putri  Faculty of Computer Science, Universitas Pembangunan Panca Budi, Medan, Indonesia
  • Andysah Putera Utama Siahaan  Ph.D. Student of School of Computer and Communication Engineering, Universiti Malaysia Perlis, Kangar, Malaysia
  • Fachrid Wadly  Faculty of Computer Science, Universitas Pembangunan Panca Budi, Medan, Indonesia
  • Muslim  Faculty of Computer Science, Universitas Pembangunan Panca Budi, Medan, Indonesia

Keywords:

Shortest Path, Haversine, Masjid

Abstract

An image is a medium for conveying information. The information contained therein may be a particular event, experience or moment. Not infrequently many images that have similarities. However, this level of similarity is not easily detected by the human eye. Eigenface is one technique to calculate the resemblance of an object. This technique calculates based on the intensity of the colors that exist in the two images compared. The stages used are normalization, eigenface, training, and testing. Eigenface is used to calculate pixel proximity between images. This calculation yields the feature value used for comparison. The smallest value of the feature value is an image very close to the original image. Application of this method is very helpful for analysts to predict the likeness of digital images. Also, it can be used in the field of steganography, digital forensic, face recognition and so forth.

References

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International Journal of Scientific Research in Science and Technology

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Published

2017-08-31

Issue

Volume 3, Issue 6, July-August-2017

Section

Research Articles

License

Copyright (c) IJSRST

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Nadya Andhika Putri, Andysah Putera Utama Siahaan, Fachrid Wadly, Muslim, " Image Similarity Test Using Eigenface Calculation, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 3, Issue 6, pp.510-514, July-August-2017.