Visual detection of particulates in processed meat products by x ray

Thomas F. Schatzki; Richard Young; Ron P. Haff; J. Eye; G. Wright

doi:10.1117/12.198888

6 January 1995 Visual detection of particulates in processed meat products by x ray

Thomas F. Schatzki, Richard Young, Ron P. Haff, J. Eye, G. Wright

Proceedings Volume 2345, Optics in Agriculture, Forestry, and Biological Processing; (1995) https://doi.org/10.1117/12.198888
Event: Photonics for Industrial Applications, 1994, Boston, MA, United States

Abstract

A test has been run to study the efficacy of detecting particulate contaminants in processed meat samples by manual observation of line-scanned x-ray images. Six hundred processed product samples arriving over a 3 month period at a national USDA-FSIS laboratory were scanned at 230 cm²sec with 0.5 X 0.5 mm resolution, using 50 KV, 13 ma excitation, with digital interfacing and image correction. Images were inspected off-line, using interactive image enhancement. Forty percent of the samples were spiked, blind to the analyst, in order to establish the manual recognition rate as a function of sample thickness [1 - 10 cm] and texture of the x-ray image [smooth/textured], as well as spike composition [wood/bone/glass], size [1 - 4 mm] and shape [splinter/round]. The results have been analyzed using maximum likelihood logistic regression. In meat packages less than 6 cm thick, 2 mm bone chips are easily recognized, 1 mm glass splinters with some difficulty, while wood is generally missed even at 4 mm. Operational feasibility in a time-constrained setting has bee confirmed. One half percent of the samples arriving from the field contained bone slivers > 1 cm long, one half percent contained metallic material, while 4% contained particulates exceeding 3.2 mm in size. All of the latter appeared to be bone fragments.

Citation Download Citation

Thomas F. Schatzki, Richard Young, Ron P. Haff, J. Eye, and G. Wright "Visual detection of particulates in processed meat products by x ray", Proc. SPIE 2345, Optics in Agriculture, Forestry, and Biological Processing, (6 January 1995); https://doi.org/10.1117/12.198888

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