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Background Modeling Using Temporal-Local Sample Density Outlier Detection Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Content Aware Image Size Reduction Using Low Energy Maps for Reduced Distortion

Authors : Pooja Solanki, Charul Bhatnagar, Anand Singh Jalal, Manoj Kumar

Published in: Proceedings of International Conference on Computer Vision and Image Processing

Publisher: Springer Singapore

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Abstract

On different devices images are often viewed with different resolutions which require image resizing. Resizing images often affects the quality of the images. To better resize images to different resolutions content aware image resizing should be done so that important features are preserved. Seam carving is one such content aware image resizing technique. In this work seam carving is used to downsize an image. This is achieved by carving out an optimal seam (either vertical or horizontal), which contains less information. Each seam removes a pixel from every row (or column) to reduce the height (or width) of the image. To prevent distortion resulting from uniform seam carving, we propose an algorithm that uses a new energy gradient function. In this method minimum of three neighboring pixels is calculated in both energy map and cumulative map and these values are added to find the value of pixel for the new cost matrix.

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Metadata
Title
Content Aware Image Size Reduction Using Low Energy Maps for Reduced Distortion
Authors
Pooja Solanki
Charul Bhatnagar
Anand Singh Jalal
Manoj Kumar
Copyright Year
2017
Publisher
Springer Singapore
Book
Proceedings of International Conference on Computer Vision and Image Processing

Print ISBN: 978-981-10-2103-9

Electronic ISBN: 978-981-10-2104-6

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-981-10-2104-6_42