CCD Machine Vision Rice Grain Quality Analyzer Inspection System

Inspection principle

This type of rice quality inspection machine is connected to the rice processing production line, and to the rice lifting and conveying pipelines. The rice is extracted from the conveying pipeline at regular intervals and the quality of the rice is analyzed. It can analyze rice germination grains, heterogeneous germ grains, grass seeds, insect-eaten grains, Gibberella grains, damaged grains, black germ grains, impurities to improve the quality of rice, and form statistical reports from time to time to improve product safety and traceability.

When it is detected that the quality of the rice sampled is not good, the operators of the production line can adjust the parameters of the rice sorting machine on the production line in time to ensure the quality of the rice produced. The detected rice can be automatically sent back to the rice processing line through the pipeline, and the grains are returned to the warehouse without wasting.

Equipment advantages&details

Using the KEYE Rice Appearance Quality Tester, each analysis image, distribution map and result data can be saved, and the analysis results can be output to an Excel sheet. The measurement error of the length and width of the equipment is ≤±0.05mm, the error of the whole rice rate is ≤±1.0%, and the precision is high; and the system can manually delete abnormal rice, the data can be automatically updated, and the inspection is more accurate, which can be used for the quality inspection of imported rice In the evaluation, control the rice quality.

Key technology

Combine traditional machine vision methods and artificial intelligence algorithms to analyze rice. First, use traditional vision methods to segment the rice grains in the video frame, and then use artificial intelligence algorithms to identify the attributes of the segmented rice grains 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 rice, and the properties of the two sides were analyzed. Through the registration algorithm, the front and back of the rice are registered one by one, and their respective attributes are combined to obtain the attributes of a complete rice grain.

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 rice is smoother, fast and robust High advantages.

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

3. Rice attribute recognition algorithm: 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.

Advantages of CCD visual

1)High detection accuracy and fast detection efficiency:CCD visual inspection equipment uses machine control according to the system, with small error and high detection rate.

2)Wide detection range to detect cosmetic defects and dimensional measurements:The multi-station inspection method can accurately measure the outline, specifications, appearance defects, product aspect ratio and other performance parameters of the product to be inspected at one time.

3)Improve product quality and error rates:Vision inspection equipment is based on system control, which can distinguish good products from bad products through automatic inspection technology, and then automatically place them in different parts.

4)Save labor costs and enable high repetitive work:CCD visual inspection can work stably for a long time, it is difficult for human eyes to observe the same object for a long time, and machine vision can perform measurement, analysis and recognition tasks for a long time. And it can continue to work, with low requirements for the natural environment of the application, in addition to saving product costs, it also greatly improves productivity.

5)Improve company competitiveness and employee safety factor:Non-contact detection, which does not cause any damage to observers and observers, improves the reliability of the system. Machine vision technology guarantees the ultimate human-machine interaction technology, which ensures a better and safer workplace.