The objective of this research was to design and fabricate a compact, cost effective multispectral instrument and to
collect and analyze spectra for real-time contaminant detection for poultry processing plants. The prototype system
developed in this research consisted of a multispectral imaging system, illumination system and an industrial portable
computer. The dual-band spectral imaging system developed in this study was a two-port imaging system that consisted
of two identical monochrome cameras, optical system and two narrow bandpass filters whose center of the wavelength
are 520 and 560 nm with 10 nm FWHM, respectively. A spectral reflectance from a chicken carcass was collected and
split in two directions by an optical system including a beamsplitter and lenses, and then two identical collimated lights
were filtered by the narrow bandpass filters and delivered to the cameras. Lens distortions and geometric misalignment
of the two cameras were mathematically corrected.
The prototype system was tested at the real-time processing line and the preliminary results showed that the dual-band
spectral imaging system could effectively detect feces and ingesta on the surface of poultry carcass.
A prototype real-time multispectral imaging system for fecal and ingesta contaminant detection on broiler carcasses has been developed. The prototype system includes 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, ceca, and colon) and ingesta 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. The UML models included class, object, activity, sequence, and collaboration diagram. User interface model included seventeen inputs and six outputs. A window based real-time image processing software composed of eleven 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 is reliable for the harsh environments and UML based image processing software is flexible and easy to be updated when additional parameters are needed for in-plant trials.
The objective of this research is to design and fabricate a compact, cost effective multispectral instrument and to collect
and analyze spectra for real-time contaminant detection for poultry processing plants. It was revealed by our previous
research that the fecal contamination on the surface of the poultry carcass could be detected by sensing the spectral
reflectance of the carcass surface in two specific wavelengths, namely 517 nm and 565 nm. The prototype system
developed in this research consists of a multispectral imaging system, illumination system and handheld PC. To
develop the system cost-effectively, all components are selected from off-the-shelf products and manually assembled.
The multispectral imaging sensor developed in this research is a two-port imaging system that consists of two identical
monochrome cameras, optical system and two narrow bandpass filters whose center of the wavelength are 520 and 560
nm, respectively. A spectral reflectance from a chicken carcass is collected and split in two directions by an optical
system including a beamsplitter and lenses, and then two identical collimated lights are filtered by the narrow bandpass
filters and delivered to the cameras. Lens distortions and geometric misalignment of the two cameras are
mathematically compensated to register two images perfectly.
The prototype system is tested in the real environment and shows that it can effectively detect feces and ingesta on the
surface of poultry carcasses.
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