Border Tracing Method for Low-Power Image Processing
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Solution Overview
Problem
Existing border detection algorithms are complex and resource-intensive, making them challenging to implement on devices with limited computing power, such as mobile phones, especially for real-time video processing, which affects battery life and efficiency.
Innovation Solution
A method for border detection in images that forms contiguous blocks of pixel positions, estimates border direction perpendicular to differing pixel conditions, and uses linear interpolation to store border locations, allowing for efficient tracing and reduced energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex border detection algorithms are used to achieve accurate border detection, then measurement precision is improved, but use of energy and device complexity increase
Solution Approach 1:
The patent segments the image processing task by focusing only on border regions rather than processing the entire image. It identifies and processes only those pixel blocks where borders are likely to occur, dividing the computational workload into manageable segments that consume less energy while maintaining detection accuracy.
Solution Approach 2:
The patent applies local quality by using different processing strategies for different regions of the image. It applies border detection algorithms only to specific blocks where borders are detected, rather than uniformly processing all image regions, thereby reducing overall energy consumption while preserving local detection precision.
2Measurement precision
If complex border detection algorithms are used to achieve accurate border detection, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent reduces algorithmic complexity by segmenting the image into blocks and applying border detection only where necessary. This divides a potentially complex global processing task into simpler local operations that can be executed more efficiently on resource-constrained devices.
Solution Approach 2:
The patent applies partial action by performing border detection only on specific image blocks where borders are detected, rather than applying complex algorithms to the entire image. This partial processing approach maintains detection accuracy while reducing the overall computational complexity and resource requirements.
3Productivity
If border detection is performed on real-time video to improve productivity, then productivity is improved, but use of energy and processing power increase
Solution Approach 1:
The patent enables real-time video processing by segmenting each video frame into blocks and applying border detection only to relevant blocks. This segmentation approach reduces the computational load per frame, allowing real-time processing while minimizing energy consumption on battery-powered devices.
Solution Approach 2:
The patent applies partial processing by focusing computational resources only on blocks where borders are detected in real-time video streams. This selective processing maintains high productivity for real-time applications while reducing overall energy consumption compared to processing entire video frames uniformly.
Data Source
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AI summary
A method for scanning for borders in an image represented by pixels, the method including a first operation comprising: estimating an attribute for each of a first set of two adjacent pixel positions in the image; assessing whether a predetermined binary condition differs in respect of the two pixel positions, and if so determining that a border is present in the part of the image represented by pixels at those positions; and if a border is determined to be present in that part of the image, estimating the direction of the border as being perpendicular to a line joining the positions of the two pixels; and initiating tracing the border in that direction.