Linear Mark Detection Using Multi-Width Filter Banks
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Solution Overview
Problem
Existing linear mark detection systems can only detect marks of a predetermined width, limiting their ability to recognize marks with varying widths in an image.
Innovation Solution
A system that calculates filter values for each pixel across multiple linear mark widths, selects the most suitable feature value from these calculations, and outputs it as a feature value corresponding to the mark, allowing for the detection of marks with different widths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed predetermined width is used for linear mark detection, then the detection process is simple and fast, but the system can only detect linear marks of that specific width and cannot detect marks with varying widths
Solution Approach 1:
The patent applies dynamics by making the detection system adaptable to different mark widths through multiple filter banks, each tuned to different widths. The system dynamically selects which filter bank to use based on the detected mark width, transforming a static single-width detector into a dynamic multi-width detector that can adapt to varying conditions in the image.
Solution Approach 2:
The patent changes the parameter of filter width to enable detection of multiple mark widths. By creating multiple filter banks with different width parameters and selectively applying them based on detected mark characteristics, the system can detect linear marks of varying widths without being constrained to a single predetermined width.
2Measurement precision
If multiple filter banks for different mark widths are used, then detection accuracy for various widths improves, but processing time and computational load increase
Solution Approach 1:
The patent applies preliminary action by first detecting the width of the linear mark before applying the appropriate filter bank. This preliminary width detection step allows the system to pre-select which filter bank to use, avoiding the need to process through all possible filter banks and thereby reducing overall processing time while maintaining detection accuracy.
Solution Approach 2:
The system dynamically selects and switches between different filter banks based on the detected mark width. This dynamic selection mechanism ensures that only the relevant filter bank for the current mark width is applied, optimizing processing efficiency while maintaining high detection accuracy for marks of various widths.
Data Source
AI summary
A linear mark detection system includes a filter value calculation unit, a filter value threshold processing unit, and a feature value output unit. The filter value calculation unit calculates, for each pixel of an image, filter values corresponding to each of a plurality of linear mark widths using pixel values inside and outside the linear mark. The filter value threshold processing unit selects the most suitable value from filter values corresponding to each of the plurality of linear mark widths as a feature value. The feature value output unit outputs, for each pixel of the image, the feature value computed by the filter value threshold processing function as the feature value corresponding to the linear mark.