Detection of Content-Aware Image Resizing Using Seam Properties

Seung Jin Ryu; Hae Yeoun Lee; Heung Kyu Lee

doi:10.4028/www.scientific.net/AMM.284-287.3074

Paper Titles

Building a Post-Search Academic Search Engine Based on a Serial of Clustering Methods
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Building a Multi-Classifier System in a GA-Based Learning Environment
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Combined Probabilistic and Possibilistic Used to a Build Type-2 Fuzzy Clustering Algorithm Model
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Data Mining Based Intelligent System for Voting Behavior Analysis
p.3070

Detection of Content-Aware Image Resizing Using Seam Properties
p.3074

Efficient Hardware Architecture for Kernel Fuzzy C-Means Algorithm
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Enhanced Artificial Intelligence Algorithm for Optimal Unit Commitment Problem
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Estimation of Distribution Algorithms with Matrix Transpose in Bayesian Learning
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Exploring the Factor Effect of Learning Vector Quantization in Artificial Neural Networks
p.3097

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 284-287Detection of Content-Aware Image Resizing Using...

Detection of Content-Aware Image Resizing Using Seam Properties

Abstract:

Visually convincing content-aware image resizing, which preserves semantically important image content, has been actively researched in recent years. This paper proposes a resizing detector that reveals the trace of seam carving and seam insertion. To unveil the evidence of seam carving, we exploit energy bias of seam carved images. In addition, the correlation between adjacent pixels is analyzed to estimate the inserted seams. Empirical evidence from a large database of test images demonstrates the superior performance of the proposed detector under a variety of settings.

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Periodical:

Applied Mechanics and Materials (Volumes 284-287)

Pages:

3074-3078

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.284-287.3074

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Online since:

January 2013

Authors:

Seung Jin Ryu, Hae Yeoun Lee, Heung Kyu Lee

Keywords:

Content-Aware Image Resizing, Image Forensics, Seam Carving, Seam Insertion

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