@inproceedings{4b3da14a5923470e81d1626d26557fe7,
title = "A Visible Fluorescence Method Induced by UV Radiation for Detection of Infestation in Canary Beans",
abstract = "The proposed study aims to present an algorithm for the detection of infestation of canary beans of the species 'Phaseolus Vulgaris' by generating a visible fluorescence under UV radiation, which allows the bean to be distinguished as healthy or infested. Currently, since many of the symptoms of infestation cannot be detected by the human eye, the beans sample analysis is highly subjective. The proposed method uses images of the beans taken under UV radiation within a hermetic enclosure. Then the image is acquired and an image segmentation algorithm is executed in order to identify the beans. Each bean is labeled so that the infestation can be detected by an algorithm based on histogram analysis. For the validation of the proposed method, several samples were evaluated and the results were compared with those obtained by two experts through an exhaustive visual analysis. The results were expressed through specificity and sensitivity, obtaining 99.78\% for specificity and 90.70\% for sensitivity.",
keywords = "canary bean, detection, image processing, infestation, sensitivity, specificity, UV radiation, visible fluorescence",
author = "\{Angel Salirrosas\}, Miguel and Gianmarco Galv{\'a}n and Guillermo Kemper",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE Sciences and Humanities International Research Conference, SHIRCON 2018 ; Conference date: 20-11-2018 Through 22-11-2018",
year = "2018",
month = dec,
day = "27",
doi = "10.1109/SHIRCON.2018.8593072",
language = "Ingl{\'e}s",
series = "Proceedings of the 2018 IEEE Sciences and Humanities International Research Conference, SHIRCON 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "Proceedings of the 2018 IEEE Sciences and Humanities International Research Conference, SHIRCON 2018",
}
