Developments of automated pork carcass grading method using artificial intelligence image analysis

Juntae Kim; Byoung-Kwan Cho

doi:10.1117/12.2621142

30 May 2022 Developments of automated pork carcass grading method using artificial intelligence image analysis

Juntae Kim, Byoung-Kwan Cho

Proceedings Volume PC12120, Sensing for Agriculture and Food Quality and Safety XIV; PC1212007 (2022) https://doi.org/10.1117/12.2621142
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States

Abstract

This study was conducted to confirm the localization possibility of the automated pork carcass grading machines in Korea. This experiment has used a total of 174 carcasses. Image analysis was conducted in three main steps: 1) image preprocessing, 2) feature extraction, 3) regression model build-up. For features extraction and model building, we used the U-net and Gaussian processing regression respectively. The Analysis was done for prediction of LMP and seven different prime cuts. The prediction results were satisfactory to the European minimum standards thus making the localization of the pork carcass grading machine possible.

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Citation Download Citation

Juntae Kim and Byoung-Kwan Cho "Developments of automated pork carcass grading method using artificial intelligence image analysis", Proc. SPIE PC12120, Sensing for Agriculture and Food Quality and Safety XIV, PC1212007 (30 May 2022); https://doi.org/10.1117/12.2621142

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