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How the latest advances in image recognition technology for ADAS can save lives

Humans are fallible, and behind the wheel of a fast moving car a single moments lapse in concentration can lead to deadly mistakes.

Image recognition technology can deliver significant safety advantages as part of Advanced Driver Assistance Systems (ADAS). From lane departure warning to pedestrian and small object detection, the technology is enabling car manufacturers to meet the requirements of current and future regulations specified by the European New Car Assessment Program (Euro NCAP).

Vehicle safety bodies such as EuroNCAP have identified the potential benefits of Advanced Driver Assistance Systems (ADAS) that rely on image recognition to identify hazards and highlight these to the driver or automatically activate systems such as emergency braking. These include Forward Collision warning (FCW) and Autonomous Emergency Braking (AEB), which have been part of EuroNCAP tests since 2014.

How the latest advances in image recognition technology for ADAS can save lives

Between 2015 and 2018, EuroNCAP will introduce new tests for Speed Assistance Systems (SAS) including traffic-sign recognition as well as protection linked to AEB for Vulnerable Road Users (VRU) such as pedestrians and cyclists. New-car assessment programs in major markets worldwide, such as China and Australasia, are expected to become aligned with Euro NCAP protocols by 2018.

As expectations increase, system developers need access to cost-effective dedicated processors that are capable of delivering real-time performance while consuming only minimal power and generating little heat.

Historically, image-recognition systems have not been designed with automotive applications in mind. The design approaches established for traditional image-recognition applications such as gaming or security systems have been extensively software based, typically running on a high-performance Digital Signal Processor (DSP) running at high-megahertz frequencies.

Toshiba has created an image-recognition processor architecture that makes extensive use of hardware and firmware integration to streamline the execution of frequently-used algorithms, and to allow scalability to handle increasing numbers of applications simultaneously. This scalability enables designers to meet the most rigorous all-around vision-oriented driver-assistance protocols put forward by Euro NCAP.

Click here to learn more about implementing ADAS image recognition systems

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