|Heitschmidt, Gerald - Jerry|
Submitted to: Computers and Electronics in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/16/2011
Publication Date: 10/15/2011
Citation: Yoon, S.C., Park, B., Lawrence, K.C., Windham, W.R., Heitschmidt, G.W. 2011. Line-scan hyperspectral imaging system for real-time inspection of poultry carcasses with fecal material and ingesta. Computers and Electronics in Agriculture. 79:159-168.
Interpretive Summary: Chicken carcasses contaminated in poultry processing plants can carry foodborne pathogens that make people ill. This paper reports new developments in a real-time imaging system for automated detection of fecal material during high-speed poultry processing. The researchers developed a prototype multispectral imaging system built upon a hyperspectral camera so that the system can detect tiny amounts of fecal matter (down to 5-mg spots) at the line speeds up to 140 birds per minute necessary for commercial deployment. The current maximum evisceration line speed set by the USDA is 140 birds per minute. The imaging system consisted of a line-scan hyperspectral camera sensing the visible and near-infrared spectral range, line lights, and real-time application software. The most unique component of the system was the pushbroom line-scan hyperspectral imaging camera that was refined for real-time detection of feces on chicken carcasses moving at high speed. Another unique feature was the application software written in-house for real-time camera operation and triggering/detection algorithm execution. An image-based triggering algorithm was developed to determine start and end positions of birds for image formation. The imaging system with a portable platform can be easily installed in commercial poultry processing plants. A speed test performed in a pilot-scale processing facility showed that the system could handle up to 180 birds per minute. Typical fecal materials (duodenum, ceca, colon) and ingesta were used for the study. The performance of fecal detection was comparable to what the previous research achieved. The imaging platform showed its potential use in commercial poultry processing lines.
Technical Abstract: In poultry processing plants, fecal material and ingesta are the primary source of carcass contamination with microbial pathogens. The current practice of the poultry inspection in the United States is primarily human visual observations. Since the visual inspection is becoming more challenging in poultry processing plants adopting high-speed lines, a rapid sorting system could significantly improve the detection and monitoring of carcasses with surface fecal material and ingesta. As a result, we developed a prototype line-scan hyperspectral imaging system configured as a real-time multispectral imaging subsystem for online detection of surface fecal material and ingesta. Specifically, we integrated a commercially available off-the-shelf hyperspectral image camera into the system with two line lights and a custom software program for real-time multispectral imaging. The bottleneck of the imaging system was the data acquisition. For that reason, a multithreaded software architecture was designed and implemented not only to meet the application requirements such as speed and detection accuracy, but also to be customizable to different imaging applications such as systemic disease detection in the future. The image acquisition and processing speed tests confirmed the system could operate to scan poultry carcasses in commercial poultry processing plants. The fecal detection algorithm was based on the previous research using different hyperspectral imaging systems. A new carcass detection and image formation algorithm was developed to allow existing image processing and detection algorithms reusable without any modifications. Sixteen chicken carcasses and four different types of fecal and ingesta samples were used in a study to test the imaging system at two different speeds (140 birds per minute and 180 birds per minute) in a pilot-scale poultry processing facility. The study found that the system could grab and process three waveband images of carcasses moving up to 180 birds per minute (a line-scan rate 286 Hz) and detect fecal material and ingesta on their surfaces. The detection accuracy of the system varied between 89% and 98% with minimum false positive errors (less than 1%), depending on tested detection algorithms. Therefore, these findings provide the basis of not only a commercially viable imaging platform for fecal detection but also a single poultry inspection system for multiple tasks such as systemic disease detection and quality sorting.