AI-based image signal processing tuning system
VeriSilicon has announced AcuityPercept, its AI-based automatic image signal processing (ISP) tuning system, designed to intelligently optimise image processing parameters for enhanced object recognition.
AcuityPercept enhances the accuracy and efficiency of AI perception systems by dynamically optimising image signal processing tuning parameters through automated tuning processes. It is broadly applicable to AI-powered vision applications across various industries, including autonomous driving, robotic vision, and AIoT. Here, ISP ensures that acceptable images are generated under diverse lighting conditions to ensure accurate object recognition.
Leveraging a global directive and local refinement algorithms, AcuityPercept employs metadata and loss feedback from AI task models to automatically achieve optimal image signal processing tuning. By continuously refining ISP settings, it effectively enhances object detection accuracy and delivers optimal ISP-processed images for neural network processing. Combining AcuityPerceptwith VeriSilicon’s image signal processing IP enables automated closed-loop optimisation.
“AcuityPercept is a key ISP tuning system that bridges the ISP with the target AI perception engine to achieve optimal object recognition. As AI-driven perception becomes increasingly critical in autonomous vehicles, smart surveillance, and robotics, our AI-powered automatic ISP tuning system lays the foundation for more accurate, efficient, and scalable AI vision,” said Weijin Dai, Chief Strategy Officer, Executive Vice President, and General Manager of the IP Division at VeriSilicon. “AcuityPercept has demonstrated excellent results with road data collected by our automotive ISP customers. It is a crucial technology that enables vision perception engines to clearly and reliably identify objects.”
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