Abstract
Automatic image cropping techniques are particularly important to improve the visual quality of cropped images and can be applied to a wide range of applications such as photo-editing, image compression, and thumbnail selection. In this paper, we propose a saliency-based image cropping method which produces significant cropped images by only relying on the corresponding saliency maps. Experiments on standard image cropping datasets demonstrate the benefit of the proposed solution with respect to other cropping methods. Moreover, we present an image selection method that can be effectively applied to automatically select the most representative pages of historical manuscripts thus improving the navigation of historical digital libraries.
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Acknowledgment
We gratefully acknowledge the Estense Gallery of Modena for the availability of the digitized historical manuscripts used in this work. We also acknowledge the CINECA award under the ISCRA initiative, for the availability of high performance computing resources and support.
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Cornia, M., Pini, S., Baraldi, L., Cucchiara, R. (2018). Automatic Image Cropping and Selection Using Saliency: An Application to Historical Manuscripts. In: Serra, G., Tasso, C. (eds) Digital Libraries and Multimedia Archives. IRCDL 2018. Communications in Computer and Information Science, vol 806. Springer, Cham. https://doi.org/10.1007/978-3-319-73165-0_17
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DOI: https://doi.org/10.1007/978-3-319-73165-0_17
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