Artificial Vision
The artificial vision is a technology that enable to provide "senses" to lines and supply chains.

What can contribute an artificial vision system?

Endow to quality controls with high accuracy and reproducibility. They are systems able to recognize, through various sensors, all variables that govern a process. All of it without the need of human intervention.

Being able to detect and differentiate different elements using codes OCR or 2D codes in assembly lines. Even for simple elements is able to detect and classify according to shapes through recognition algorithms.

The main advantage of these systems. Increase the efficiency of production lines and production processes providing 'eyes’ to workstations, through sensors and cameras. It is a way to add intelligence to the production process, being able to react to changes, foreseen or unforeseen, and auto-regulate.

Thanks to recent advances in miniaturization and cost reduction these systems can be implemented in consumer products. Allowing designers and engineers to provide to their products new functionalities 3.0.

Types of artificial vision

OCR Reader and 2D codes
Read and obtain information marked on the piece or item
Pattern Recognition
Using sensors they detect a pattern in the environment previously selected. The pattern can be visual, infrared, sonorous, electronic, magnetic field,...
Colour Selector
It is capable to detect elements of a defined RGB Colour with the accuracy required
Can recognize the number of preset items that are in its field of view

How does an artificial vision system behaves?

1. Image Acquisition

At first the system sensors (visual, infrared, magnetic field,…) acquire information from the outside, what we call 'image'.

2. Database reading

It is the memory system. It can be libraries, images, and patterns inter alia.. It finds the proper pattern to compare with the image.

3. Comparison

Suitable algorithms for each application are responsible to process image and pattern.

4. Create outputs or system reaction

According to the result of comparing it will create the system outputs that have been previously defined. Or in the case of more advanced systems those tha the system has learned.


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