Dedicated ASIC Offloads Image Processing to Reduce Power
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Solution Overview
Problem
Conventional computing devices face challenges in efficiently processing high-resolution images and 3D image capture due to high power consumption and computational resource requirements, leading to reduced battery life and performance.
Innovation Solution
Integration of a dedicated processor component, such as an ASIC or DSP, to offload image processing tasks from the general-purpose processor, enabling local processing of image data and reducing the need for continuous high-power processing by the device processor.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution cameras and 3D image capture are provided, then imaging data quality and functionality are improved, but power consumption and computational resource requirements increase
Solution Approach 1:
The patent segments image processing tasks between a dedicated processor component and the device processor. The dedicated processor handles initial image computational processing (such as gesture detection, object recognition) while the device processor handles higher-level processing only when needed, based on thresholds. This segmentation reduces the overall power consumption while maintaining imaging quality.
Solution Approach 2:
The dedicated processor component acts as an intermediary between the camera system and the device processor. It pre-processes image data and determines when further processing is necessary, reducing the burden on the power-consuming device processor while preserving the ability to handle high-resolution and 3D imaging data.
2Measurement precision
If high-resolution cameras and 3D image capture are provided, then imaging data quality and functionality are improved, but computational resource requirements increase
Solution Approach 1:
The patent divides computational processing into two levels: initial processing by the dedicated processor component (handling gesture detection, object recognition) and secondary processing by the device processor (handling complex analysis only when thresholds are met). This segmentation reduces the computational burden on the device processor while maintaining the ability to process high-resolution and 3D imaging data.
3Productivity
If the device processor continuously processes image data, then processing performance is improved, but battery life is reduced
Solution Approach 1:
The dedicated processor component performs preliminary image processing and evaluation before the device processor is activated. It pre-processes image data, detects gestures or objects of interest, and determines whether further processing is necessary based on predefined thresholds. This preliminary action allows the device processor to remain in standby mode most of the time, significantly extending battery life while maintaining processing performance when needed.
Solution Approach 2:
Instead of continuous processing by the device processor, the system uses periodic action where the device processor is activated only when the dedicated processor determines that processing thresholds are met. This periodic activation based on actual needs significantly reduces power consumption while maintaining the ability to process images at high performance when required.
4Use of energy by moving object
If the device processor remains in standby mode, then power consumption is reduced, but processing capability is limited
Solution Approach 1:
The dedicated processor component serves as an intermediary that maintains processing capability even when the device processor is in standby mode. It continuously processes image data for basic functions (gesture detection, object recognition) and activates the device processor only when higher-level processing is needed, thus maintaining overall processing capability while minimizing power consumption.
Data Source
AI summary
Approaches are described for managing the processing of images or video on a computing device. A portable computing device can include one or more dedicated components, such as an application-specific integrated circuit (ASIC) or other dedicated processor component, to be integrated into the computing device to perform at least a portion of the imaging processing of captured images or video. For example, the dedicated processor component can enable the offloading of basic image signal processing, as well as higher level or “machine vision” processing from the device processor of the device. In this way, the dedicated processor component can perform signal processing for which the input is an image (or video), and where image or video data can be analyzed, interpreted and/or manipulated to generate an output, the output of image processing being either an image or a set of characteristics or parameters related to the image. The output can be provided to a device processor for further processing.