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 17 inputs and 6 outputs. 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 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.