@inproceedings{3dd422f225bf424bbbdaaa42153b141f,
title = "Reaching behind Specular Highlights by Registration of Two Images of Broiler Viscera",
abstract = "The manual postmortem inspection of broilers and their viscera is becoming a bottleneck as the slaughter rate increases. Computer vision can assist veterinarians during the inspection, but specular highlights can hide crucial details when inspecting for diseases on the viscera set. This study aims to restore details behind these specular highlights by capturing two images of the same viscera using shifting light positions. The dataset consists of images captured in-line at a poultry processing plant. The method achieves an average SSIM score of 0.96 over a test set of 100 image sets. The result is visually pleasing images with correct textural information instead of specular highlights.",
author = "Anders J{\o}rgensen and Malte Pedersen and Rikke Gade and Jens Fagertun and Moeslund, {Thomas B.}",
year = "2019",
month = jun,
doi = "10.1007/978-3-030-21074-8_30",
language = "English",
isbn = "978-3-030-21073-1",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "357--372",
editor = "Gustavo Carneiro and Shaodi You",
booktitle = "Computer Vision – ACCV 2018 Workshops",
address = "Germany",
note = "Asian Conference on Computer Vision ; Conference date: 02-12-2018 Through 06-12-2018",
}