Paper
23 October 2006 Poultry carcass inspection by a fast line-scan imaging system: results from in-plant testing
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Proceedings Volume 6381, Optics for Natural Resources, Agriculture, and Foods; 63810V (2006) https://doi.org/10.1117/12.686144
Event: Optics East 2006, 2006, Boston, Massachusetts, United States
Abstract
During in-plant testing of a hyperspectral line-scan imaging system, images were acquired of wholesome and systemically diseased chickens on a commercial processing line moving at a speed 70 birds per minute. A fuzzy logic based algorithm using four key wavelengths, 468 nm, 501 nm, 582 nm, 629 nm, was developed using image data from the validation set of images of 543 wholesome and 66 systemically diseased chickens. A classification method using the fuzzy logic based algorithm was then tested on the testing set of images of 457 wholesome and 37 systemically diseased chickens, as well as 80 systemically diseased chickens that were imaged off-shift during breaks between normal processing shifts of the chicken plant. The classification method correctly identified 89.7% of wholesome chicken images and 98.5% of systemically diseased chicken images in the validation set. For the testing data set, the method correctly classified 96.7 % of 457 wholesome chicken images and 100% of 37 systemically diseased chicken images. The 80 images acquired off-shift were also 100% correctly identified.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kuanglin Chao, Chun-Chieh Yang, Yud-Ren Chen, Diane E. Chan, and Moon S. Kim "Poultry carcass inspection by a fast line-scan imaging system: results from in-plant testing", Proc. SPIE 6381, Optics for Natural Resources, Agriculture, and Foods, 63810V (23 October 2006); https://doi.org/10.1117/12.686144
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KEYWORDS
Fuzzy logic

Line scan image sensors

Imaging systems

Inspection

Algorithm development

Image processing

Hyperspectral imaging

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