Quality Grain Quality Analyzer Lab Sorting Equipment For Coffee Bean

The green beans before roasting are generally called (Green). If the quality of the green beans is not good, no matter how hard you try to roast them, you will not be able to brew a beautiful coffee. The green beans are usually exported from the origin two months after harvesting. This year's crop is called New Crop. After a year called Past Crop. And after a longer period of time is called Old Crop. coffee beans are crops, freshness will naturally affect its taste. With fresh green beans, you can enjoy the distinct characteristics and vibrant flavors of their various varieties. Take rice as an example, if it is left for a long time, its original flavor will fade with the loss of water. Fresh green beans are distinguished by their bright green color. Except for freshness. Regardless of the variety, you should try to choose raw beans with larger particles and no color spots.

The high-precision oat defect analyzer developed and produced by our company can be used in oat processing plants, oat storage, laboratories, and quality inspection centers. It can detect and analyze oats germination grains, heterogeneous germ grains, grass seeds, worm-eaten grains, gibberellins, broken grains, black germs, impurities, etc., and generate statistical reports from time to time to improve product safety and traceability Ability, and at the same time can guide the improvement of the quality of oats.

Combine traditional machine vision methods and artificial intelligence algorithms to analyze oats. First, use traditional vision methods to segment the oats in the video frame, and then use artificial intelligence algorithms to identify the attributes of the segmented oats to determine whether there are insects. Moth, sprouting, mildew and other problems. At the same time, two high-resolution cameras were used to photograph the front and back of the coffee bean, and the properties of the two sides were analyzed. Through the registration algorithm, the front and back oats are registered one by one, and their respective attributes are combined to obtain the attributes of a complete oat grain.

Equipment configurations

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 oats is smoother, fast and robust High advantages.

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

3. Coffee beans attribute recognition algorithm: adopts a lightweight neural network and integrates a semi-supervised learning method. The model can be iteratively optimized only by annotating a small amount of data. It has the advantages of high accuracy, fast speed, and convenient deployment.

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