Saliency-Based Adaptive Object Extraction for Color Underwater Images

DOI

10.2991/iccsee.2013.661How to use a DOI?

Keywords

underwater image, object extraction, saliency map, retinex

Abstract

Because of the special optical underwater imaging environment, the contrast and quality of images are affected severely, causing it difficult to extract objects from underwater images. An adaptive underwater object extraction method based on the saliency maps is proposed in this paper. Firstly, preprocessing method is utilized to improve the color contrast and quality. Then multi-scale image features are combined into a single topographical saliency map. The most salient image location and primary object are directed by the saliency map. By calculating the Bhattacharyya distance of salient features between the primary object and background, the adaptive weights of conspicuity maps can be obtained, as well more accurate object can be extracted from the fuzzy images. Experiment results show that the proposed method can not only detect the objects effectively but also extract more accurate object areas. It has a better performance compared with other algorithms.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Huibin Wang
AU  - Xin Dong
AU  - Jie Shen
AU  - Xuewen Wu
AU  - Zhe Chen
PY  - 2013/03
DA  - 2013/03
TI  - Saliency-Based Adaptive Object Extraction for Color Underwater Images
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 2651
EP  - 2655
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.661
DO  - 10.2991/iccsee.2013.661
ID  - Wang2013/03
ER  -