Vision For Future
Machine Vision Applications
Machine Vision Systems capture images of every item on production lines and automate many industrial inspections, including visual inspections for surface and dimensional defects, presence-absence checks, product type verifications, and code readings.
Positioning and Robotic Guidance
You can determine the exact position and orientation of parts and transfer the results directly to robots or position correction systems.
Identification
It covers a range of machine vision applications that include reading printed characters -OCR-, pattern matching, and decoding 1D or 2D barcodes on products.
Measurements
Calculates the distances between two or more points on an object, the distances between points to certain geometric positions, or the perimeter or area of geometric shapes and determines whether these measurements meet tolerances.
Surface Defect Controls
Surface detection tools find faults such as pollution, scratches, cracks, stains, discolorations, gaps, dents, which are vital for quality control.
Machine Vision Applications:
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Presence/Absence check
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Automated measurement and testing
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Barcode reading
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Color verification
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Flaw detection
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OCR & OCV
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Part verification
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Pattern matching
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Extraction
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Traceability
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Vision guided robotics
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Level detection
Machine Vision Benefits
Machine Vision Systems serve to optimize production or assembly lines, minimize human intervention in critical processes, ensure quality, and improve overall output.
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Due to its speed, accuracy and repeatability, Machine Vision Systems ensure that repetitive tasks are performed with high performance in production lines. For example, on a production line, machine vision system can inspect hundreds or even thousands of parts per minute. Machine Vision Systems built on the right camera resolution and optics can easily examine object details that are too small to be seen by the human eye.
Machine Vision System Details
Machine Vision System is a combination of industrial cameras, optical design and image processing software.
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Selection of the Machine Vision System camera according to the field of view and pixel resolution. The type of application also plays an important role in camera selection. For example, the camera used for robotic guidance and the camera used for surface inspection should have the different characteristics.
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Optical selection for Machine Vision Systems should be made according to the environment brightness, surface reflection and most importantly, the type of the application.
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Machine Vision System software must include image processing and analysis algorithms, and must be fast enough to complete operations in milliseconds, be easy to use, and provide accurate results.
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Machine Vision Implementation Approaches
Finding the object or feature of interest within the camera's field of view is the critical first step in any machine vision application.
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Finding the object of interest often determines success or failure in the results. If image processing algorithms can't pinpoint the target image, they can't orient, identify, examine, count, or measure the part. Finding the object of interest in the image sounds simple, but differences in real production environments can make this step extremely difficult.
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In order to guarantee success in all our applications, we use advanced algorithms, set the target clearly, and get high-performance results.
