JOURNAL ARTICLE

Cluster-based saliency-guided content-aware image retargeting

Kang LiChing Yu TsengChao Long JhengMing-Fang WengChao Yung Hsu

Year: 2017 Journal:   Journal of Electronic Science and Technology Vol: 15 (2)Pages: 141-146   Publisher: Elsevier BV

Abstract

Straightforward image resizing operators without considering image contents (e.g., uniform scaling) cannot usually produce satisfactory results, while content-aware image retargeting aims to arbitrarily change image size while preserving visually prominent features. In this paper, a cluster-based saliency-guided seam carving algorithm for content-aware image retargeting is proposed. To cope with the main drawback of the original seam carving algorithm relying on only gradient-based image importance map, we integrate a gradient-based map and a cluster-based saliency map to generate a more reliable importance map, resulting in better single image retargeting results. Experimental results have demonstrated the efficacy of the proposed algorithm.

Keywords:
Seam carving Retargeting Image (mathematics) Computer science Artificial intelligence Computer vision Content (measure theory) Cluster (spacecraft) Image manipulation Pattern recognition (psychology) Mathematics

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Topics

Visual Attention and Saliency Detection
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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