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29 December 2000 Fusion of visible and X-ray sensing modalities for the enhancement of bone detection in poultry products
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Proceedings Volume 4203, Biological Quality and Precision Agriculture II; (2000) https://doi.org/10.1117/12.411744
Event: Environmental and Industrial Sensing, 2000, Boston, MA, United States
Abstract
The U.S. demand for deboned chicken has risen greatly in the past 5 years, with the expectations that this demand will only continue at an accelerated level. The standard inspection process for bones in meat is for workers to manually feel for bones. It is clear that this time- consuming manual inspection method is insufficient to meet the increasing demand for deboned meat products. Georgia Tech Electrical Engineering faculty and Research Scientists in conjunction with a leading x-ray equipment manufacturer are working together on the development of a system to fuse information from visible images and x-ray images to enhance the accuracy of detection. Currently there are some bones that x-ray systems have difficulty detecting. These are usually relatively thin and are located near the surface of the meat. A primary example is a fanbone (so called because of its shape). We will describe and present results from work geared towards the development of an integrated system that would fuse visible and x-ray information. Significant benefits to the poultry industry are anticipated in terms of reduced processing costs, improved inspection performance and increased throughput through the use of the integrated system to be described. Additionally, generic aspects of the proposed technologies may be applicable to other food processing industries.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
George Vachtsevanos, Wayne D. Daley, Bonnie S. Heck, Anthony Yezzi, and Yuhua Ding "Fusion of visible and X-ray sensing modalities for the enhancement of bone detection in poultry products", Proc. SPIE 4203, Biological Quality and Precision Agriculture II, (29 December 2000); https://doi.org/10.1117/12.411744
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