Paper Info
Title
Optimized image resizing using flow-guided seam carving and an interactive genetic algorithm
Abstract
In this paper, we introduce a novel method for content-aware image resizing based on flow-guided seam carving. It extends the existing seam carving framework by replacing the conventional energy field with a "structure-aware" energy field that takes into account the feature orientations in the image. Guided by this new energy field, our approach excels in preserving (i.e., avoiding the distortion of) important structures in the image, such as shape boundaries. We also present a simple user interface to further optimize the resizing result based on the genetic selection process among multiple resizing operators such as scaling, cropping, and flow-guided seam carving. We show that such simple user interaction, coupled with the genetic algorithm, dramatically increases the chances of producing the user-desired outcome.
Year
DOI
Venue
2014
10.1007/s11042-012-1242-6
Multimedia Tools and Applications
Keywords
Field
DocType
Image resizing,Structure-aware energy field,Interactive genetic algorithm
Computer vision,Computer graphics (images),Resizing,Computer science,Flow (psychology),Seam carving,Artificial intelligence,Operator (computer programming),User interface,Scaling,Distortion,Genetic algorithm
Journal
Volume
Issue
ISSN
71
3
1380-7501
Citations 
PageRank 
References 
0
0.34
21
Authors
4
Name
Order
Citations
PageRank
Jong-chul Yoon112712.52
Sun-Young Lee29612.49
In-kwon Lee350351.14
Henry Kang445417.87