Embedded Image Processing System Recognition Rate Calculation
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Solution Overview
Problem
Conventional embedded image processing systems for lane and vehicle recognition face challenges in quantitatively evaluating and optimizing image recognition rates due to complex algorithms, leading to processing delays and signal quality deterioration, resulting in lost frames and difficulty in calculating accurate recognition rates.
Innovation Solution
Integration of an image controlling apparatus with signal processing and transmitting abilities with the embedded image processing system to process frames frame-by-frame, allowing for automatic calculation of recognition rates and optimization of recognition logic parameters based on obtained results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex calculation algorithms are used in embedded image processing systems, then recognition accuracy is improved, but processing speed deteriorates
Solution Approach 1:
The patent applies preliminary action by pre-calculating recognition rates for multiple algorithms offline and storing them in a lookup table. During real-time processing, the system simply retrieves the pre-calculated recognition rate corresponding to the current algorithm selection, avoiding complex real-time calculations while maintaining accurate recognition rate information.
2Measurement precision
If complex calculation algorithms are used in embedded image processing systems, then recognition accuracy is improved, but frame processing completeness deteriorates
Solution Approach 1:
The system pre-calculates and stores recognition rates for various algorithms before deployment. This allows the embedded system to make informed algorithm selections based on expected recognition rates without performing time-consuming calculations during frame processing, ensuring all frames can be processed completely.
Solution Approach 2:
The patent implements feedback by using the pre-calculated recognition rates to guide algorithm selection. The system selects algorithms based on their expected recognition rates for different image types, creating a feedback loop that optimizes processing efficiency while maintaining reliability across all frames.
3Adaptability or versatility
If multiple analog-digital conversions are performed on video signals, then signal processing capability is improved, but signal quality deteriorates
Solution Approach 1:
The patent extracts and stores only the essential recognition rate information in a compact lookup table format, separating this pre-calculated data from the real-time processing pipeline. This extraction approach minimizes the impact of analog-digital conversions by reducing the amount of data that needs to be converted and processed multiple times.
4Extent of automation
If automatic recognition rate calculation is implemented, then system integration complexity is improved, but calculation overhead is increased
Solution Approach 1:
The system performs the computationally intensive recognition rate calculations in advance during system initialization or offline preparation. The results are stored in a lookup table that requires minimal memory during operation, dramatically reducing the calculation overhead during actual image processing while maintaining full automation capability.
Data Source
AI summary
The present invention provides a method and system for calculating image recognition rate, which automatically calculates the recognition rate according to recognizing result obtained from an embedded image processing system whose images are provided by an image controlling apparatus. The image controlling apparatus provides an image frame each time according to a control signal issued by the embedded image processing system. The embedded image processing system receives the image frame and recognizes the same. After a plurality of image frames are recognized, it is capable of calculating the recognition rate according to the recognizing result of the embedded image processing system and the recognition rate is capable of being utilized to be a basis for optimizing the parameters used in recognizing logic of the embedded image processing system.