@inproceedings{dfcfa89dcc634c7fbe05c8dcbfbe82ac,
title = "Accurate, swift and noiseless image binarization",
abstract = "In this paper, we will present an accurate, swift and noiseless image binarization technique that was tested on real life back side container images. Our approach consists of converting a colored image to a grayscaled one, then to construct the histogram which will be divided into group of colors and after that, the foreground - that can be darker or lighter than the background - will be automatically identified and finally, the foreground boundaries will be assiduously enhanced before creating the binarized image. The average processing time of our proposed method is around 0.8 milliseconds which makes it highly suitable for real life multi-user applications.",
keywords = "Container Number, automatic foreground detection, binarized Image, histogram",
author = "Wassim Al-Khawand and Seifedine Kadry and Riccardo Bozzo and Khaled Smaili",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; International Conference on Computer Vision and Image Analysis Applications, ICCVIA 2015 ; Conference date: 18-01-2015 Through 20-01-2015",
year = "2015",
month = dec,
day = "9",
doi = "10.1109/ICCVIA.2015.7351908",
language = "English",
series = "Proceedings - International Conference on Computer Vision and Image Analysis Applications, ICCVIA 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "Proceedings - International Conference on Computer Vision and Image Analysis Applications, ICCVIA 2015",
address = "United States",
}