Circle Segment Detection Using Adaptive Resolution Accumulators
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Solution Overview
Problem
Current circle detection methods in driver assistance systems face challenges in achieving real-time processing and low resource/energy consumption, particularly when used on standard hardware like smartphones, due to high energy consumption and computational intensity.
Innovation Solution
The method involves detecting gradients, scaling gradient vectors with respective radii, and accumulating endpoints in accumulator arrays with reduced resolution for larger radii, allowing for faster processing and reduced memory requirements, thereby eliminating the need for specialized hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution accumulator arrays are used for circle detection, then detection precision is improved, but processing time increases and energy consumption increases
Solution Approach 1:
The patent segments the circle detection process by creating multiple accumulator arrays with different resolutions, each dedicated to detecting circles of specific radius ranges. Small-radius circles use high-resolution arrays for precision, while large-radius circles use low-resolution arrays for speed, eliminating the need to process all data at maximum resolution.
Solution Approach 2:
Different regions of the parameter space (radius ranges) are assigned different quality levels (resolutions). The patent applies high resolution locally to small-radius circle detection and low resolution locally to large-radius circle detection, optimizing the trade-off between precision and speed for each specific detection task.
2Measurement precision
If high-resolution accumulator arrays are used for circle detection, then detection precision is improved, but memory requirements increase
Solution Approach 1:
The patent divides the single large high-resolution accumulator array into multiple smaller arrays with different resolutions. This segmentation reduces the total memory footprint while maintaining high-resolution detection capability for small circles, as each array only stores data for its specific radius range.
Solution Approach 2:
Memory resources are allocated efficiently by assigning high resolution (more memory) only where needed (small-radius detection) and low resolution (less memory) where less precision is required (large-radius detection), optimizing overall memory utilization.
3Device complexity
If standard hardware is used for circle detection, then device complexity is reduced, but processing speed decreases
Solution Approach 1:
The patent changes the resolution parameter of accumulator arrays based on the radius parameter being detected. This parameter adaptation allows standard hardware to achieve high processing speeds for large circles (using low-resolution arrays) while maintaining adequate precision for small circles, eliminating the need for specialized high-performance hardware.
Data Source
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AI summary
A circular segment detection device is configured to detect gradients, yielding gradient vectors, and to scale these gradient vectors by their respective radii. The resulting endpoints of these scaled gradient vectors are then accumulated in accumulator arrays assigned to those radii. The resolution of the accumulator arrays decreases as the radius increases.