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Proceedings Paper

Multispectral imaging for detecting contamination in poultry carcasses
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Paper Abstract

A multispectral imaging system with selected optical filters of 542 and 700-nm wavelength was shown feasible for detecting contaminated poultry carcasses with high accuracy. The analysis of textural features based on co-occurrence matrix (COM) was conducted to determine the performance of multispectral image analyses in discriminating unwholesome poultry carcasses from wholesome carcasses. The variance, sum average, sum variance, and sum entropy of COM were the most significant texture features (P less than 0.0005) to identify unwholesome poultry carcasses. The feature values of angular second moment, variance, sum average, sum variance, and sum entropy did not vary with the distances and directions of COM for the spectral images. When a direction was equal to 0 degrees, the contrast was lower and the inverse difference moment and difference variance were higher (P less than 0.01) than any other direction in the visible spectral images. The characteristics of variance and sum variance texture feature of spectral images varied with the wavelength of spectral images and unwholesomeness of poultry carcasses as well. The sum variance of wholesome was higher (P less than 0.005) than unwholesome carcasses at the spectral image of 542-nm. The linear discriminant model was able to identify wholesome carcasses with classification accuracy of 83.9 percent and the unwholesome carcasses could be identified by quadratic model with 97.1 percent accuracy when textural features of spectral image at 700-nm wavelength were used as input data for models.

Paper Details

Date Published: 12 January 1999
PDF: 10 pages
Proc. SPIE 3544, Pathogen Detection and Remediation for Safe Eating, (12 January 1999); doi: 10.1117/12.335776
Show Author Affiliations
Bosoon Park, USDA Agricultural Research Service (United States)
Yud-Ren Chen, USDA Agricultural Research Service (United States)
Kevin Chao, USDA Agricultural Research Service (United States)

Published in SPIE Proceedings Vol. 3544:
Pathogen Detection and Remediation for Safe Eating
Yud-Ren Chen, Editor(s)

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