Blotch Detection in Archive Films Based on Visual Saliency Map
Degradations frequently occur in archive films that symbolize the historical and cultural heritage of a nation. In this study, the problem of detection blotches commonly encountered in archive films is handled. Here, a block-based blotch detection method is proposed based on a visual saliency map. T...
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Online Access: | http://dx.doi.org/10.1155/2020/5965387 |
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doaj-529987c74d9345228c51ff650c8594902020-11-25T02:21:36ZengHindawi-WileyComplexity1076-27871099-05262020-01-01202010.1155/2020/59653875965387Blotch Detection in Archive Films Based on Visual Saliency MapYildiz Aydin0Bekir Dizdaroğlu1Department of Computer Engineering, Erzincan Binali Yildirim University, Erzincan 24000, TurkeyDepartment of Computer Engineering, Karadeniz Technical University, Trabzon 61080, TurkeyDegradations frequently occur in archive films that symbolize the historical and cultural heritage of a nation. In this study, the problem of detection blotches commonly encountered in archive films is handled. Here, a block-based blotch detection method is proposed based on a visual saliency map. The visual saliency map reveals prominent areas in an input frame and thus enables more accurate results in the blotch detection. A simple and effective visual saliency map method is taken into consideration in order to reduce computational complexity for the detection phase. After the visual saliency maps of the given frames are obtained, blotch regions are estimated by considered spatiotemporal patches—without the requirement for motion estimation—around the saliency pixels, which are subjected to a prethresholding process. Experimental results show that the proposed block-based blotch detection method provides a significant advantage with reducing false alarm rates over HOG feature (Yous and Serir, 2017), LBP feature (Yous and Serir, 2017), and regions-matching (Yous and Serir, 2016) methods presented in recent years.http://dx.doi.org/10.1155/2020/5965387 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yildiz Aydin Bekir Dizdaroğlu |
spellingShingle |
Yildiz Aydin Bekir Dizdaroğlu Blotch Detection in Archive Films Based on Visual Saliency Map Complexity |
author_facet |
Yildiz Aydin Bekir Dizdaroğlu |
author_sort |
Yildiz Aydin |
title |
Blotch Detection in Archive Films Based on Visual Saliency Map |
title_short |
Blotch Detection in Archive Films Based on Visual Saliency Map |
title_full |
Blotch Detection in Archive Films Based on Visual Saliency Map |
title_fullStr |
Blotch Detection in Archive Films Based on Visual Saliency Map |
title_full_unstemmed |
Blotch Detection in Archive Films Based on Visual Saliency Map |
title_sort |
blotch detection in archive films based on visual saliency map |
publisher |
Hindawi-Wiley |
series |
Complexity |
issn |
1076-2787 1099-0526 |
publishDate |
2020-01-01 |
description |
Degradations frequently occur in archive films that symbolize the historical and cultural heritage of a nation. In this study, the problem of detection blotches commonly encountered in archive films is handled. Here, a block-based blotch detection method is proposed based on a visual saliency map. The visual saliency map reveals prominent areas in an input frame and thus enables more accurate results in the blotch detection. A simple and effective visual saliency map method is taken into consideration in order to reduce computational complexity for the detection phase. After the visual saliency maps of the given frames are obtained, blotch regions are estimated by considered spatiotemporal patches—without the requirement for motion estimation—around the saliency pixels, which are subjected to a prethresholding process. Experimental results show that the proposed block-based blotch detection method provides a significant advantage with reducing false alarm rates over HOG feature (Yous and Serir, 2017), LBP feature (Yous and Serir, 2017), and regions-matching (Yous and Serir, 2016) methods presented in recent years. |
url |
http://dx.doi.org/10.1155/2020/5965387 |
work_keys_str_mv |
AT yildizaydin blotchdetectioninarchivefilmsbasedonvisualsaliencymap AT bekirdizdaroglu blotchdetectioninarchivefilmsbasedonvisualsaliencymap |
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