Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Pork intramuscular fat content nondestructive testing method based on computer vision

A computer vision, intramuscular fat technology, applied in computing, image data processing, instruments, etc., can solve problems such as lack of comprehensive consideration

Active Publication Date: 2016-06-22
CHINA AGRI UNIV
View PDF7 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Pork intramuscular fat content nondestructive testing method based on computer vision
  • Pork intramuscular fat content nondestructive testing method based on computer vision
  • Pork intramuscular fat content nondestructive testing method based on computer vision

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0104] In order to further explain the technical means and effects that the present invention adopts to achieve the intended purpose of the invention, below in conjunction with the accompanying drawings and preferred embodiments, the specific implementation, structure, features and effects of the present invention will be described in detail as follows: back.

[0105] like figure 1 Shown is a non-destructive detection method for pork intramuscular fat content based on computer vision, comprising the following steps:

[0106] (1) Calibrate the camera to obtain the actual length of the unit pixel in the image corresponding to the real scene;

[0107] (2) Select the longissimus dorsi muscle (commonly known as eye muscle) at the 5th to 6th ribs of pork as a sample, place the sample on a black background cloth, and use a white LED light to fill in the light on the sample, and use a digital camera to scan the sample horizontally. The cross-section is taken from above to obtain th...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

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...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06T7/00
CPCG06T7/0004G06T2207/30128
Inventor 郑丽敏张彧龙田立军李爽
Owner CHINA AGRI UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products