Home News Axis launches the 7th generation of ARTPEC chip
Axis launches the 7th generation of ARTPEC chip
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Axis launches the 7th generation of ARTPEC chip

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Axis launched the 7th generation of its ARTPEC chip, that will power an array of new capabilities and features to Axis network cameras. These features include even better imaging, enhanced security features, powerful compression and a possibility to run impressive analytics on the edge.

The chip developed by Axis, provides a layer of control that is crucial for effective cybersecurity. Going forward, the new chip will be the basis for the vast majority of Axis network video products.

“In the current market situation, we believe Axis has a strong competitive advantage as one of only a few manufacturers with our own system-on-chip,” says Johan Paulsson, Chief Technology Officer. “We have complete control over every single transistor, which is very good from a trust and cybersecurity perspective. Plus, unlike other chips, it’s not a generic all-purpose design. Rather, it’s 100% optimized for creating high-quality Axis network video solutions.”

With a completely redesigned image processing pipeline, the chip further improves all the signature Axis technologies that have been created to address difficult light conditions. ARTPEC-7 enables “built-in” security features for Axis cameras, including signed firmware so only secure authorized firmware can be installed, and secure boot, which prevents the booting of unauthorized firmware.

Future Axis cameras will also let users choose between H.264 and H.265 video encoding depending on what best suits their system and surveillance needs. Either encoding standard in combination with Axis Zipstream technology will now require even lower bandwidth and storage space without sacrificing image quality. In addition, users are free to reevaluate their choice of codec at any time if their requirements should change.

Finally, this chip features a real-time object detection engine that will make it possible for Axis and Axis partners to develop powerful analytics to automatically detect and differentiate between people, faces and objects.

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