Green Coffee Beans Quality Analyzer Visual Inspection Machine for Tea.coffee

Product Specification

Inspection principle

Coffee is a beverage made from roasted and ground coffee beans. As one of the three major beverages in the world, it is the main beverage popular in the world along with cocoa and tea.

Coffee trees are perennial evergreen shrubs or small trees in the Rubiaceae family. Coffee for daily drinking is made with coffee beans and various cooking utensils. Coffee beans refer to the nuts in the fruit of the coffee tree. A cup of standard coffee should not taste bitter. A qualified barista will rigorously perform every step when making coffee, and finally the coffee presented to the guests will be presented in the taste. Different degrees of sweetness, acidity, mellowness or cleanliness.

The laboratory coffee bean quality analyzer developed and produced by our company. This machine can replace manual work and can work 7*24 hours. It can detect the quality of coffee beans with high precision. Insect-eaten beans, gibberellins, broken beans, spotted beans, impurities, etc. are tested and analyzed, and statistical reports are formed from time to time to improve product safety and traceability. The contact parts between the equipment and the sample are made of medical-grade materials, which are safe and hygienic, with intelligent design, simple operation and convenient maintenance.

Key technology:

1. Automatic binarization: Use deep neural network to segment the foreground and background of the image. Compared with the traditional binarization method, it can be applied to a variety of lighting conditions, and the edge segmentation of coffee beans is smoother, fast and robust The advantage of high sex.

2. Adhesive coffee bean segmentation algorithm: The method based on connected domains cannot segment the adhered coffee beans. The deep neural network is used to segment the adhered coffee beans at an instance level, which can reach a speed of 1000fps and can process the adhered coffee beans in real time.

3. Coffee bean attribute recognition algorithm: adopts lightweight neural network and integrates semi-supervised learning method. Iterative optimization of the model can be carried out with only a small amount of data marked by the user. It has the advantages of high accuracy, fast speed, and convenient deployment.

The analyzer combines traditional machine vision methods and artificial intelligence algorithms to analyze coffee beans. First, the traditional visual method is used to segment the coffee beans in the video frame, and then the artificial intelligence algorithm is used to identify the attributes of the segmented coffee beans. Determine whether there are moth-eaten, sprouting, moldy and other problems. At the same time, two high-resolution cameras were used to photograph the front and back of the coffee beans, and the properties of the two sides were analyzed. Through the registration algorithm, the front and back coffee beans are registered one by one, and their respective attributes are combined to obtain the attributes of a complete coffee bean.

Equipment advantages:

1. High accuracy, artificial intelligence AI detection, the error is controlled within 0.01%;

2. High efficiency, 2 minutes to complete the test, one is equivalent to 3 manual workers;

3. Intelligent, three-dimensional, easy to operate, you can use it in 3 minutes;

4. Femto-visible, high-precision camera omni-directional detection 0.04mm recognition accuracy;