Submitted to: Sensing and Instrumentation for Food Quality and Safety
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/31/2007
Publication Date: 3/6/2007
Citation: Park, B., Kise, M., Lawrence, K.C., Windham, W.R., Smith, D.P., Thai, C.N. 2007. Real-Time Multispectral Imaging System for Online Poultry Fecal Inspection using Unified Modeling Language.. Sensing and Instrumentation for Food Quality and Safety. 1(2):45-54. Interpretive Summary: Fecal contaminations are a food safety risk because of high correlation between feces and pathogenic bacteria. Food Safety Inspection Service (FSIS) is pursuing a broad and long-term science-based strategy to improve the safety of poultry and poultry products to better protect public health. The ARS has developed an imaging system for fecal and ingesta contaminant detection on broiler carcasses. In order to implement real-time imaging system in a harsh environmental poultry processing plant, the system design factors for both hardware and software were investigated. Particularly, real-time image processing software was developed for increasing detection accuracy and decreasing errors. The test results of industrial-scale real-time system demonstrated that the multispectral imaging technique was able to detect fecal contaminants with a commercial processing speed (currently 140 birds per minute). This industrial-scale imaging system can improve the FSIS poultry safety inspection program by incorporating scientific testing and efficacy of fecal detection during poultry processing.
Technical Abstract: A prototype real-time multispectral imaging system for fecal detection on broiler carcasses has been developed. The prototype system included a common aperture camera with three optical trim filters (517, 565 and 802-nm wavelength), which were selected by visible/NIR spectroscopy and validated by a hyperspectral imaging system with decision tree algorithm. The on-line testing results showed that the multispectral imaging technique can be used effectively for detecting feces (from duodenum, cecum, and colon) on the surface of poultry carcasses with a processing speed of 140 birds per minute. This paper demonstrated both multispectral imaging hardware and real-time image processing software. For the software development, the unified modeling language (UML) design approach was used for on-line application. A window based real-time image processing software composed of 11 components, which represented class, architecture, and activity. Both hardware and software for a real-time fecal detection were tested at the pilot-scale poultry processing plant. The run-time of the software including online calibration was fast enough to inspect carcasses on-line with an industry requirement. Based on the preliminary test at the pilot-scale processing line, the system was able to acquire poultry images in real-time. According to the test results, the imaging system was reliable for the harsh environments and UML based image processing software was flexible and easy to be updated when additional parameters were needed for in-plant trials.