Image Processor Evaluation Layer Software Hardware Precision
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Solution Overview
Problem
Conventional image processing systems face inefficiencies in processing raw image data for gesture recognition and other machine vision applications, particularly in combining software and hardware implementations to achieve optimal precision and real-time processing.
Innovation Solution
An image processor with multiple layers, including a preprocessing layer, an evaluation layer, and a recognition layer, where the evaluation layer combines software-implemented and hardware-implemented portions to generate object data of varying precision levels, enabling efficient processing and delivery of output data for gesture recognition and other applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If software algorithms are used for evaluation layer processing, then measurement precision is improved, but processing speed deteriorates
Solution Approach 1:
The evaluation layer is segmented into software-implemented portion and hardware-implemented portion, each handling different precision requirements. The software portion processes data requiring high precision while the hardware portion handles real-time processing with lower precision requirements, resolving the contradiction between precision and speed through functional segmentation.
Solution Approach 2:
The patent introduces a hybrid architecture dimension that combines software and hardware implementations within the same evaluation layer. This allows simultaneous operation of high-precision software algorithms and high-speed hardware algorithms on different data streams or different stages of processing, effectively adding a dimensional solution to the precision-speed tradeoff.
2Speed
If hardware algorithms are used for evaluation layer processing, then processing speed is improved, but measurement precision deteriorates
Solution Approach 1:
The evaluation layer is divided into hardware-implemented portion for speed-critical processing and software-implemented portion for precision-critical processing. This segmentation allows the system to optimize for speed where applicable while maintaining precision where required, eliminating the need to choose one over the other exclusively.
Solution Approach 2:
Different precision levels are applied locally to different portions of the evaluation layer based on specific processing requirements. The hardware algorithm provides sufficient precision for real-time response while the software algorithm provides enhanced precision for final object data, ensuring each component operates at the appropriate quality level for its function.
3Adaptability or versatility
If only software implementation is used, then adaptability is improved, but productivity deteriorates
Solution Approach 1:
The patent merges software implementation and hardware implementation within the evaluation layer, combining the adaptability advantages of software with the productivity advantages of hardware. This hybrid approach allows the system to maintain software flexibility for algorithm updates while achieving hardware-level processing throughput for real-time performance.
Solution Approach 2:
The evaluation layer is designed with multi-functionality, capable of operating in different modes (software-only, hardware-only, or hybrid) depending on the specific application requirements. This universal design allows the same architecture to serve both adaptive software-driven applications and high-throughput hardware-driven applications.
4Productivity
If only hardware implementation is used, then productivity is improved, but adaptability deteriorates
Solution Approach 1:
The patent combines hardware implementation with software implementation in the evaluation layer, allowing the system to leverage hardware productivity for real-time processing while maintaining software adaptability for algorithmic flexibility. The hybrid architecture enables both high throughput and easy adaptation to different processing requirements.
Solution Approach 2:
The evaluation layer is designed dynamically, allowing the system to adjust the balance between hardware and software processing based on real-time requirements. This dynamic configuration enables the system to optimize for either productivity or adaptability depending on the specific operational context, rather than being fixed in one mode.
Data Source
AI summary
An image processor comprises image processing circuitry implementing a plurality of processing layers including at least an evaluation layer and a recognition layer. The evaluation layer comprises a software-implemented portion and a hardware-implemented portion, with the software-implemented portion of the evaluation layer being configured to generate first object data of a first precision level using a software algorithm, and the hardware-implemented portion of the evaluation layer being configured to generate second object data of a second precision level lower than the first precision level using a hardware algorithm. The evaluation layer further comprises a signal combiner configured to combine the first and second object data to generate output object data for delivery to the recognition layer. By way of example only, the evaluation layer may be implemented in the form of an evaluation subsystem of a gesture recognition system of the image processor.