@inproceedings{d3997674019e463191285a0b744ad7d2,
title = "Content-Based cropping using visual saliency and blur detection",
abstract = "This research presents an automatic image/frame cropping scheme to preserve the regions of interest in imagery data. First, a blur detection based on Structural Similarity (SSIM) is proposed to identify whether an image contains a blurred background and the sharp foreground objects can then be extracted. The visual saliency is further calculated to help remove insignificant boundaries. Some pre-defined rules are employed to determine more appropriate cropping limits. If further reduction of resolution is necessary, the resulting image after cropping will be scaled directly to the target size. The experimental results show that the proposed method is computationally efficient and the promising results can be achieved in still images and video frames.",
keywords = "blur detection, content-based cropping, retargeting, saliency, SSIM",
author = "Chou, {Yung Chieh} and Fang, {Chih Yun} and Su, {Po Chyi} and Chien, {Yu Chien}",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 10th International Conference on Ubi-Media Computing and Workshops, Ubi-Media 2017 ; Conference date: 01-08-2017 Through 04-08-2017",
year = "2017",
month = oct,
day = "18",
doi = "10.1109/UMEDIA.2017.8074087",
language = "???core.languages.en_GB???",
series = "Ubi-Media 2017 - Proceedings of the 10th International Conference on Ubi-Media Computing and Workshops with the 4th International Workshop on Advanced E-Learning and the 1st International Workshop on Multimedia and IoT: Networks, Systems and Applications",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "Ubi-Media 2017 - Proceedings of the 10th International Conference on Ubi-Media Computing and Workshops with the 4th International Workshop on Advanced E-Learning and the 1st International Workshop on Multimedia and IoT",
}