AI Inspection Rice Grain Quality Analyzer with Stainless 304 Food Grade

Product Specification

Rice quality AI visual detector

The rice quality AI visual detector developed and produced by our company can replace manual labor and perform 7*24 hours of high-precision inspection of rice quality. Detect and analyze the normal grains,germinated grains, heterogeneous buds, grass seeds, chalky grains, insect-eaten grains, gibberella grains, large broken grains, small broken grains, black germ grains, impurities, etc. of rice, and form statistical reports 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:

• Automatic binarization: Use deep neural network to segment the foreground and background of the image, compared with the traditional binarization method, Automatic binarization can be applied to a variety of lighting conditions, and have the advantages of smoother edge of the rice segmentation, fast and robust High.
• Adhesion rice segmentation algorithm: The connected domain-based method cannot segment adhesion rice. The deep neural network is used to segment the adhesion rice at an instance level, which can reach a speed of lOOOfps and can process the adhesion rice in real time.

The example diagram is as follows

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

The detector combines traditional machine vision methods and artificial intelligence algorithms to analyze rice. First, traditional visual methods are used to segment the rice grains in the video frame, and then artificial intelligence algorithms are used to identify the attributes of the divided rice grains and judge Whether there are insect erosion, germination, mold and other problems. At the same time, two high-resolution cameras were used to photograph the front and back of the rice, and the properties of the two sides were analyzed. Through the algorithm, align the front and back of the rice one by one, and combine their respective attributes to synthesize the attributes of a complete rice.

Equipment advantages:

1. High accuracy, artificial intelligence AI detection, the error is controlled within 0.5%;

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

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

4. Nano-visible, high-precision camera all-round detection 0.04mm recognition accuracy;

Equipment details&key technology

1.Automatic binarization: Use deep neural network to segment the foreground and background of the image, compared with the traditional binarization method, Automatic binarization can be applied to a variety of lighting conditions, and have the advantages of smoother edge of the rice segmentation, fast and robust High.

2.Adhesion rice segmentation algorithm: The connected domain-based method cannot segment adhesion rice. The deep neural network is used to segment the adhesion rice at an instance level, which can reach a speed of l000fps and can process the adhesion rice in real time.

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

Features of equipment

• AI algorithm: high stability, adapting to the environment and background disturbance; different defect samples can be automatically identified after training
• Dataization: Independent database, save multiple samples, analyze non-good products, and retain history
• Multi-orientation: 360 ° comprehensive inside and outside the samples
• High precision: detection accuracy can be high
• Modularization, can flexibly increase or decrease the detection function according to customer actual needs
• Easy to operate: It is easy to operate and easy to maintain
• Safety: Medical grade material manufacturing, fully compliant with medical supplies production environment