Search
📃

Optimized image resizing using flow-guided seam carving and an interactive genetic algorithm

Citation:
Jong-Chul Yoon, Sun-Young Lee, In-Kwon Lee, and Henry Kang, "Optimized image resizing using flow-guided seam carving and an interactive genetic algorithm", Multimedia Tools and Applications (SCIE), Vol. 71, No. 3, pp. 1013-1031, 2014, August 2014
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 userdesired outcome.