@inproceedings{5b4766f6bcec44afa537dfd8e922c36a,
title = "Efficient color correction method for smartphone camera-based health monitoring application",
abstract = "Smartphone health monitoring applications are recently highlighted due to the rapid development of hardware and software performance of smartphones. However, color characteristics of images captured by different smartphone models are dissimilar each other and this difference may give non-identical health monitoring results when the smartphone health monitoring applications monitor physiological information using their embedded smartphone cameras. In this paper, we investigate the differences in color properties of the captured images from different smartphone models and apply a color correction method to adjust dissimilar color values obtained from different smartphone cameras. Experimental results show that the color corrected images using the correction method provide much smaller color intensity errors compared to the images without correction. These results can be applied to enhance the consistency of smartphone camera-based health monitoring applications by reducing color intensity errors among the images obtained from different smartphones.",
author = "Duc Dang and Cho, {Chae Ho} and Daeik Kim and Kwon, {Oh Seok} and Chong, {Jo Woon}",
year = "2017",
month = sep,
day = "13",
doi = "10.1109/EMBC.2017.8036945",
language = "English",
series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "799--802",
booktitle = "2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society",
note = "null ; Conference date: 11-07-2017 Through 15-07-2017",
}