Line Detection Using Candidate Break Regions
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Solution Overview
Problem
Existing line detection algorithms in digital images often incorrectly identify multiple lines where a single line exists, due to the inability to accurately determine candidate line break regions and assign appropriate gradient amplitudes and angles.
Innovation Solution
A method that identifies candidate line break regions by comparing the gradient characteristics of pixels, assigns gradient amplitudes and angles based on adjacent pixels, and filters to determine a best-fit line component, thereby enhancing line detection accuracy and reducing false positives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional line detection algorithms are used, then line detection can be performed, but multiple lines are incorrectly identified where a single line exists
Solution Approach 1:
The patent applies preliminary action by identifying candidate line break regions before final line detection. The method pre-processes the image to locate potential break points where lines might be incorrectly segmented, then uses these pre-identified regions to guide the line detection process and prevent false positives.
Solution Approach 2:
The patent introduces an intermediary element - the candidate line break region - that mediates between the raw image data and the final line detection result. This intermediary region serves as a bridge to refine the detection process by highlighting areas that require special attention to avoid incorrect line identification.
2Measurement precision
If candidate line break regions are identified using gradient characteristics, then line detection accuracy improves, but computational complexity increases
Solution Approach 1:
The patent applies local quality by focusing computational resources on specific regions of the image - the candidate line break regions - rather than processing the entire image uniformly. By identifying and concentrating analysis on local areas where line breaks are likely to occur, the method improves accuracy without requiring complex processing of the whole image.
Solution Approach 2:
The patent segments the image processing task by dividing it into distinct stages: identifying candidate line break regions, analyzing gradient characteristics in those regions, and performing final line detection. This segmentation allows each stage to be optimized independently, reducing overall algorithmic complexity while maintaining high accuracy.
3Stability of the object's composition
If gradient amplitude and angle are assigned based on adjacent pixels, then line continuity is improved, but processing time increases
Solution Approach 1:
The patent applies partial action by assigning gradient amplitudes and angles only to pixels within candidate line break regions rather than to all pixels in the image. This partial processing approach maintains line continuity in critical areas while significantly reducing the overall processing time compared to exhaustive pixel-by-pixel analysis.
Data Source
AI summary
Certain examples described herein relate to a method for detecting a line in an image. In one such example, the method comprises identifying a candidate line break region in the image. Identifying the candidate line break region comprises identifying a first pixel of the image and a second pixel of the image, between which the candidate line break region appears, a characteristic of the first pixel and the second pixel having a predetermined similarity relationship. The method then comprises using the identified candidate line break region to assist in detecting a line in the image.