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Activity Number:
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187
- Contributed Poster Presentations: Korean International Statistical Society
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Type:
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Contributed
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Date/Time:
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Monday, July 30, 2018 : 10:30 AM to 12:20 PM
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Sponsor:
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Korean International Statistical Society
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Abstract #328685
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Title:
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How to Identify Fake Images?: Multiscale Methods vs. Sherlock Holmes
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Author(s):
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Minsu Park* and Hee-Seok Oh and Donghoh Kim and Minjeong Park and Jinae Lee
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Companies:
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Yonsei University College of Medicine and Seoul National University and Sejong University and Statistics Korea and Yonsei University College of Medicine
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Keywords:
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Wavelet packet analysis;
Handwriting analysis;
Image analysis;
LASSO
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Abstract:
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In this paper, we propose wavelet-based procedures to identify the differences of features including handwritings and images. The proposed method is based on a novel combination of multiscale methods with a regularization technique. Beverly and Caroline (2006) introduced a method of detecting forged handwriting via wavelets and statistics. We mainly expand the scope of their method to general images and improve the results considerably. Key features that distinguish the proposed method from existing ones are two-fold: (1) a multiscale framework formed by wavelets and wavelet packets gives a rich and flexible structure that allows adaptation to signals (images) with various spatial structures; and (2) a regularized regression technique is capable of handling to high-dimensional data, which might represent images of interest properly and extend the class of images considerably. We demonstrate the promising empirical evidences of the proposed method through various experiments.
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Authors who are presenting talks have a * after their name.
