A non-destructive detection method of pork intramuscular fat content based on computer vision

Abstract

The present invention relates to a pork intramuscular fat content nondestructive testing method based on computer vision. The method comprises the steps of adopting a camera calibration method to calibrate a CCD digital camera, selecting the pork musculi oculi just now purchased from a slaughter house as an experiment sample, shooting and sampling the cross-section of the pork musculi oculi, carrying out the pre-processing on an obtained sample image via an improved sample block repair method, and recovering the original information of a light reflection area of the image; combining a maximum entropy method and an iteration method to carry out the image segmentation on the pre-processed musculi oculi image, and extracting the pork marbling; extracting 291 characteristic values, such as a fat number index, a fat distribution index, a fat texture index, etc., from an obtained marbling image, establishing a pork intramuscular fat content prediction model according to the characteristic values and a chemical method detection result, and finally predicting the pork intramuscular fat content via the model. By utilizing the method of the present invention, the pork intramuscular fat content can be predicted very well, and the pork nutrition detection is more objective, more accurate and more efficient.

Description

technical field [0001] The invention relates to the technical fields of nutrition detection, pattern recognition and computer vision, in particular to a method for non-destructive detection of intramuscular fat content of pork based on computer vision. Background technique [0002] Intramuscular fat is an important factor affecting the quality of pork. The flavor and juiciness of meat continue to improve with the increase of intramuscular fat content. The tenderness of pork is mainly achieved by cutting off the cross-linking structure between muscle fiber bundles, which is beneficial to the muscle fiber during chewing. Fracture, which changes the sensory quality of the meat. Therefore, on the premise of ensuring a high growth rate and lean mass, it is also necessary to maintain an appropriate level of body fat and intramuscular fat. 2%-3% intramuscular fat content is ideal for the eating characteristics of pork. [0003] Traditional intramuscular fat content detection gene...

AI Technical Summary

Problems solved by technology

The image processing algorithm and detection device introduced in the above invention did not take into account the influence of sample surface reflection on the follow-up work, but only used median filtering and other methods for simple preprocessing, and at the same time, some of the selected eigenvalues ​​were related to the amount of fat, and some were related to fat. distribution, some are related to texture, but none of these indicators have been considered comprehensively

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