You’re likely to encounter “computer vision” (CV) and “machine vision” (MV) in relation to image processing. Although these terms are often used interchangeably, MV actually refers to the application of CV.
Computer vision refers to the automated extraction of data (information) from visual inputs. It’s a sub-discipline of artificial intelligence (AI): a sub-discipline of computer science concerned with developing artificial systems to perform tasks that would typically require human intelligence. Computer vision engineers use AI to derive insights from videos, images, et cetera. Applications include image classification, captioning, and enhancement; object detection and tracking; and text extraction.
Machine vision refers to the application of computer vision, especially in professional settings. An MV system combines CV software with hardware such as industrial equipment, allowing the latter to analyze and act on visual inputs. Applications include product inspection, quality management, predictive analytics, and facial recognition.
What are real-world examples of machine vision and computer vision?
One well-known MV solution is Apple’s “Face ID,” which employs facial recognition. Facial recognition systems use CV software to identify individuals by extracting and analyzing their facial features. This enables “Face ID” and other methods of biometric authentication: “a cybersecurity process that verifies a user's identity using their unique biological characteristics.” [1] Another example is Tesla Vision, the complex CV software behind Tesla’s trademark self-driving technology. [2]
How much does computer vision software or a machine vision system cost?
It depends on the scope of your project. Synaptiq has helped dozens of organizations develop accurate AI budgets. Clients come to us because the stakes are high, and there is no one-size-fits-all answer. We offer a variety of consulting services in this area, including low-cost, low-commitment feasibility studies to help organizations like yours gauge the scope of their project.
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Where can I learn more about computer vision and machine vision?
If you’re interested in developing CV software yourself, we recommend PyImageSearch. They cover beginner to expert-level skills, from installing OpenCV (an open-source CV software library) to solving your own projects.
If you’re interested in real-world examples of CV and MV, see our case studies:
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