Anhui Keye Information & Technology Co., Ltd.
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| Place of Origin: | China |
| Brand Name: | KEYE |
| Certification: | No |
| Model Number: | KVIS-A-Rice |
| Minimum Order Quantity: | 1 SET |
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| Price: | Negotiable |
| Packaging Details: | Fumigation-free wood |
| Delivery Time: | 4 to 6 weeks |
| Payment Terms: | L/C, T/T |
| Supply Ability: | 1 set per 4 weeks |
| False Rate: | 0.5% | Condition: | New |
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| Test Report: | Provided | Equipment Advantages: | Information Storage |
| Ket Technology: | High Performance GPU Computing And Processing Platform | Touch Screen: | Humanized HMI |
| Accuracy: | 99% | Image Capture: | Available |
| High Light: | GPU quality control lab equipment,HMI quality control lab equipment,GPU food analysis lab equipment |
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Inspection background
Machine vision technology uses image acquisition equipment such as cameras or cameras and image processing software to work together to replace the human eye for image recognition, size measurement, shape matching, etc. Its advantage is that the measurement equipment does not have subjective factors, No fatigue, consistent and fast measurements every time. The rice appearance quality detector can automatically detect the appearance quality indicators of rice and rice after obtaining the image through the scanner. Testing units, grain distribution enterprises, processing enterprises, etc.
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 milled 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. It can be used for the quality inspection of imported rice In the evaluation, control the rice quality.
Key technology
The analyzer combines traditional machine vision methods and artificial intelligence algorithms to analyze glutinous rice. First, traditional visual methods are used to segment the glutinous rice grains in the video frame, and then the artificial intelligence algorithm is used to identify the attributes of the segmented glutinous rice grains and make judgments.
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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 glutinous rice is smoother, fast and robust High advantages. |
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2. Adhesive glutinous rice segmentation algorithm: Connected glutinous rice cannot be segmented based on the method of connected domains. The deep neural network is used to segment the adhered glutinous rice at an instance level, which can reach a speed of 1000fps and can process the adhered glutinous rice in real time. |
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3. Nuomi 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. |
Machine Parameters
| Detection speed | 1000fps |
| Voltage and current | Adapt to customer national standards |
| Ambient temperature | -10℃~+45 Celsius |
| environment humidity | Below 85% (no condensation) |
| weight | 60kg |
| ODM/OEM | accept |
After-sale service
The company has a complete technical service team and rapid response mechanism, and has dedicated service specialists for each customer, who can receive technical consultation and fault reports from customers at any time. And to ensure rapid response to customer emergencies, to ensure that customers receive satisfactory service.During the epidemic or due to special reasons, when after-sales engineers are unable to reach the site, the service center can remotely adjust customer equipment for troubleshooting and technical consultation.
After the equipment arrives at the customer site, the after-sales engineer arrives in time to carry out equipment installation, commissioning, and operation training. The product quality of the whole machine is traceable, and the quality warranty period is 1 year from the date of acceptance. In the event of non-human faults during the warranty period, after-sales engineers will quickly arrive at the site or provide remote guidance for free maintenance.
Contact Person: Ms. Amy Zheng
Tel: +86 17355154206/+86 186 5518 0887
