What Is Machine Vision Image Processing?
Machine vision image processing is the analysis of images by a machine. Those with expertise in certain industries use this specific term to refer to extracting data from images for specific purposes. When professionals refer to machine vision image processing, they are often referring to the use of image analysis for controlling industrial activities or processes. While there are many other applications of machine vision, mass production is a prime example of how businesses use this kind of new technology.
Although some associate machine vision image processing with robotics, it is also frequently used in other kinds of technologies. Some of the common tasks for this technique include quality assurance, as well as sorting or handling data for all kinds of process enhancement. In general, this technology helps businesses to enhance their automated processes through automated analysis. For example, when tactile methods are not enough for robotic systems to sort through various shapes and sizes of parts, specialized machine vision image processing methods can often sort parts more efficiently, through very specific algorithms that take in the parameters of the colors or greyscale values in the image to accurately define contours or sizing for an object.
Apart from its industrial applications, using technology to understand images is very valuable for radically different kinds of technology projects. Machine vision image processing exists within a larger field sometimes known as computer vision image processing. Its use may be related to military applications, the consumer product environment, or in specific fields from medicine or transportation to asset maintenance, mechanical production, and much more.
Some of the basic tasks involved in machine vision image processing include the construction of or transformation between black-and-white or grayscale images. Engineers also work on how to achieve pattern recognition and images, or match images up with each other. It is also useful for other specific kinds of projects, such as bar coding or biometrics.
Those interested in what’s happening in this field can get more current information from leading industry periodicals, and other venues reporting on how the technique works within the larger field of artificial intelligence. Like other kinds of technology fields, the processing of images for machine vision relies on a supply chain, with hardware like 3-d lasers and software products used to create specific, scalable machine vision applications. Detailed analysis of this field can show IT experts how the vanguard is supporting progress in machine vision through this kind of image analysis and artificial data handling.
@allenJo - I agree, that would be more challenging - especially when you're talking about physical objects and not just images.
It never occurred to me that machine image processing was used to filter and sort objects as the article states. I suppose that this would be useful in assembly line processing, but it might also be useful in the post office as well.
I know that they have sorting machines in the post office but I don’t know if any of their sorters using this kind of technology. It would certainly be useful, and reduce human errors when sorting packages.
@Charred - I am by no means an expert, but I would think that pattern recognition would be the hardest thing to achieve. That’s because as humans, we see patterns in a 3 dimensional space. We look down on an image and see a pattern.
However, computers don’t “see” things as such. To a computer, everything is a stream of numbers. I understand how it would detect sequential patterns, such as the repetition of numbers in a sequence, but it would be a bit more challenging to detect spatial patterns – where’s it’s looking at something that is more three dimensional.
I am sure the algorithms exist, but I think they would be a bit more challenging.
I read a book on image processing and analysis once, and it was very fascinating. It talked about the different kinds of algorithms and methodologies for gleaning patterns from images and also manipulating them.
You see some of these algorithms used in photo editing software. For example, if you’ve ever used Photoshop or a program like it, you have the ability to manipulate images using different formulas.
Photoshop has a bunch of different algorithms, but the easiest to understand is the histogram. This basically creates a range of values for the image; for example, how many different combinations of red, white and blue exist in a photo.
This is not a transformation in itself but it’s something that Photoshop uses as a baseline when doing its transformation.
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