Automatic egg grading method based on image recognition
Through an automated method based on image recognition, combined with high-resolution cameras and uniform lighting equipment, the automatic classification of eggs is achieved, solving the problem that traditional methods cannot accurately judge the freshness of eggs, and ensuring the accuracy and credibility of grading.
CN120021568AActive Publication Date: 2025-05-23HUBEI ZHENGRENTANG TECHNOLOGY CO LTD
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Patent Information
- Application Number
- CN202510026225.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-01-08
- Publication Date
- 2025-05-23
- Estimated Expiration
- 2045-01-08
AI Technical Summary
Technical Problem
The traditional egg grading method relies on manual experience and cannot accurately judge the freshness of eggs. There are limitations in sampling and testing, which cannot cover all products.
Method used
Using an automated method based on image recognition, egg images are collected through high-resolution cameras and uniform lighting equipment, combined with image preprocessing, outer contour data fitting, weight measurement and density calculation, a functional relationship between density and freshness is established to realize the automated classification of eggs.
Benefits of technology
Accurate judgment on the freshness of eggs is achieved, illegal vendors are avoided using detection loopholes to replace inferior products, and ensure market order and consumer rights.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention discloses an automatic egg grading method based on image recognition, belongs to the technical field of image recognition detection, and aims to solve the problem that existing egg freshness detection cannot cover all products. According to the method, clear images are collected through a high-resolution camera and uniform lighting equipment, discrete point coordinates of the egg contour can be accurately extracted in combination with an advanced image preprocessing algorithm, and the relation between outer contour data and the transverse diameter and the longitudinal diameter is established by adopting an optimized ellipse fitting least square method; according to the method, the egg freshness can be accurately judged by using a high-precision electronic scale to measure the weight and performing outer contour matching and correction through an improved algorithm based on the Haushold distance, so that the egg freshness can be accurately divided according to an accurate function relationship between the density and the freshness.
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