Multispectral image textural feature-based beef tenderness detection device and method thereof

Abstract

The invention relates to a multispectral image textural feature-based beef tenderness detection device, which includes a lamp box, an illumination system, a shooting system, an object stage and a computer. The object stage is installed at the bottom of the lamp box. The shooting system includes a CCD digital camera, a multispectral filter and a camera support. The CCD digital camera is fixed on the camera support arranged at the lamp box top. The multispectral filter is loaded above a lens of the CCD digital camera, and the lens aligns with the center of the object stage surface. The computer is connected to the CCD digital camera and is used for processing and storing acquired multispectral images. The illumination system includes fluorescent lamp assemblies and halogen lamp light source assemblies. The fluorescent lamp assemblies are mounted at the bottom of the object stage to simulate natural light, and the halogen lamp light source assemblies are mounted on two sides of the lamp box top and used for auxiliary light sources. By means of the multispectral beef tenderness prediction method, effective online tenderness prediction of a beef sample can be conducted, thus laying the foundation for a future beef online quality detection system.

Description

Technical field [0001] The invention relates to a device and a method for detecting beef tenderness based on multi-spectral image texture features, and belongs to the research field of agricultural product processing and detection. Background technique [0002] Meat quality has become a growing research topic around the world. The quality of beef is the main factor that determines consumers' purchasing intention and market price. The timely detection and monitoring of beef quality during the production and circulation of beef is very important for ensuring beef food safety, promoting beef production and reasonable consumption. Role and significance. In the meat industry, the quantification of meat quality indicators has always been an important research topic. From the perspective of the highly competitive meat industry, continuous supply of meat products of excellent quality to consumers is the basic element for the survival of the majority of meat companies. The main indicat...

AI Technical Summary

Problems solved by technology

Manual evaluation is a subjective evaluation method. The evaluation personnel need to undergo special training. The evaluation process is time-consuming and labor-intensive. The evaluation results are highly subjective and poor in repeatability; although the results obtained by the shear force measurement method are objective and accurate , but the process is cumbersome and complicated, and the detection efficiency is low, which cannot meet the requirements of on-site and online detection of beef quality at all.

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