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3 Ways to Leverage the Power of Embedded Computer Vision

Nov. 8, 2023
Here’s how the advanced technology is being used in real-world applications by numerous different industries.

A technology that gives machines the ability to “see” things, embedded computer vision uses machine learning and deep learning algorithms to help users “explore” the environment. This advanced technology is already being used by several industries that rely on computer vision, or the artificial intelligence (AI) field that enables machines to extract meaningful information from digital multimedia sources.

Embedded vision systems combine both image capture and image processing capabilities into one device. “Traditional machine vision systems, on the other hand, often require a large camera and lens for image capture, along with a standardized interface and cable that transmits raw image data to a separate industrial PC,” the Association for Advancing Automation explains.

Once they have meaningful information, machines can then take actions or make recommendations based on the information that has been obtained. Computer vision differs from human sight because it recognizes only what it has been trained on and what it is designed to do exactly with certain accuracy.

Embedding AI into the Vision Process

When AI is embedded into the vision process, it trains the machines to perform supposed functions within the shortest possible processing time. This gives AI-embedded vision an upper hand over human sight—and especially when it comes to analyzing hundreds of thousands of different images within a short period of time.

“Embedded vision is one of the leading technologies with embedded AI utilized in smart endpoint applications in a wide range of consumer and industrial applications,” Suad Jusuf , Director of Product Marketing for AIoT Solutions at Renesas Electronics explains. “There are a number of value-added use cases examples, such as counting/analyzing the quality of products on a factory line, keeping a tally of people in a crowd, identifying objects and analyzing the contents of a specific area.”

Embedded vision can also be used to identify people or find cars based on VIN numbers, detect motion and perform human behavior analysis. Here are three different ways Renesas helps companies deploy AI in vision applications in the real world:

  • Smart Access Control: Security access control systems are becoming more valuable with the addition of voice and facial recognition features. Real-time recognition requires embedded systems with very high computational capabilities and on-chip hardware acceleration. To meet this challenge, Renesas provides a choice of MCU or MPU that offers very high computational power that also integrates many key features that are critical to high-performance facial and voice recognition systems such as built-in H.265 hardware decoding, 2D/3D graphic acceleration, and ECC on internal and external memory to eliminate soft-errors and allow for high-speed video processing.
  • Industrial Control: Embedded vision can be used for product safety, automation, product sorting and other activities. Using AI, machines can perform multiple operations in the production process such as packaging and distribution, thus ensuring high quality and safety during production. This helps organizations ensure high safety levels for team members working in warehouses, production plants and other facilities.
  • Transportation: Computer vision presents a large scale of ways to improve transportation services. In self-driving cars, for example, computer vision is used to detect and classify objects on the road and to create 3D maps. By using computer vision, self-driving cars gather information from the environment using cameras and sensors, which then interpret and analyze the data to make the most suitable response by using vision techniques such as pattern recognition, feature extraction and object tracking.

Right now, we’re experiencing a revolution in high-performance smart vision applications across a number of segments. The trend is well supported by the growing computational power of microcontrollers and microprocessors at the endpoints, opening great opportunities for exciting new vision applications. As frontrunners in their industry, companies like Renesas are helping organizations enhance their overall system capability with embedded AI technology that incorporates intelligent data processing at the endpoint.

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