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embedded vision

Contributor(s): Matthew Haughn

Embedded vision is the integration of computer vision in machines that use algorithms to decode meaning from observing pixel patterns in images or video. The computer vision field is developing rapidly, along with advances in silicon and, more recently, purpose-designed embedded vision processors.

Embedded vision is developing across numerous fields including autonomous medical care, agri-tech, search and rescue, and repair in conditions dangerous to humans. Applications include autonomous machines of many types such as embedded systems, driverless cars, drones, smart phones and rescue and bomb-disarming robots.

Recent developments are making the formerly power- and compute-intensive field more efficient, more effective and easier to package into even smaller electronics. Practical and increasingly powerful computer vision is enabled in an increasing number of mobile devices. Backed by cloud computing, mobile embedded vision may be capable of even greater levels of detail in processing.

An example of an embedded vision processors is that made by Synopsys. Standing to make computer vision lower in cost, lower in power and ready for smaller more mobile and embedded devices, the co-processing chip can be connected to neural networks or neural net processors to add efficient computer vision to machine learning.

This was last updated in February 2017

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