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Analysis of correlation between carcass and viscera for chicken eviscerating based on machine vision technology
Author(s) -
Chen Yan,
Ai Hui,
Li Shuo
Publication year - 2021
Publication title -
journal of food process engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.507
H-Index - 45
eISSN - 1745-4530
pISSN - 0145-8876
DOI - 10.1111/jfpe.13592
Subject(s) - evisceration (ophthalmology) , artificial intelligence , segmentation , computer vision , flock , machine vision , poultry farming , computer science , biology , medicine , pathology , paleontology , ecology , alternative medicine
In the poultry evisceration, the inconsistent position of visible carcass and invisible viscera may be one of the most neglected problems, which increase the level of visceral damage by gripping manipulator. In order to detect the position of the chicken carcass and viscera, a computer vision‐based automation system is developed to extract the region of interest from each chicken in the image acquisition system. The segmentation method of carcass is proposed by applying the color space transformation and the threshold segmentation. This method combines with several operations of morphology and reconstruction to remove the other regions such as wings and legs. After a midline abdominal incision of the chicken, the viscera is segmented using the active contour algorithm. Following data analysis, the change trend of relative position is presented between carcass and viscera. The average longitudinal deviation value of weighting 1,000–1,500 g and 1,500–2000 g chickens were 22.9 and 32.4 mm, separately. These results indicate that the relative position is significantly changed between carcass and viscera with chicken size in the longitudinal direction. In this study, machine vision technology can be satisfactorily applied to predict the position of chicken viscera, which can provide technical support for poultry processing. Practical applications For a long time, avian influenza virus and various pathogenic microorganism have been threatening the breeding and slaughtering of poultry, which can easily damage the health of people and cause widespread transmission of the virus. Therefore, automated evisceration technology by intelligent robot will become the development trend of the poultry slaughtering. However, due to the invisibility of the poultry viscera, it will easily cause damage of the internal organs during the manipulator evisceration. In this study, in order to avoid repetitive and boring work and manual operation errors, machine vision technology was introduced to automatically obtain the relative position between the visible carcass and the invisible viscera of individual chicken based on image segmentation algorithms. Thus, the position of the viscera can be predicted based on the data analysis and the carcass location, which provide useful information to guide the robot for evisceration, and it is also helpful to conduct further research in the slaughtering and processing of other poultry.