Hand Drawn Table Line Width Estimation via Histogram Analysis
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Solution Overview
Problem
Existing image processing technologies face challenges in accurately recognizing table lines on writing boards, particularly when lines are irregular due to smudges, breaks, or fades, as these irregularities are often captured as separate segments rather than a single stroke, hindering precise content extraction from images.
Innovation Solution
A method that estimates the likely width range of hand-drawn lines by generating a histogram of cross-edge widths and frequencies, allowing for the identification of irregular segments as a single stroke, which aids in merging segments, locating intersections, and determining clear regions of the line.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional image processing methods are used to detect table lines, then simple and clear lines can be recognized accurately, but irregular lines with smudges, breaks, or fades are captured as separate segments instead of a single stroke
Solution Approach 1:
The patent segments the irregular line into multiple detectable portions (clear segments) while using histogram analysis to determine the overall line width. The method divides the line detection task into: (1) identifying clear segments that can be reliably detected, (2) extracting width measurements from these segments, and (3) using statistical mode analysis to represent the entire line's width, thus resolving the contradiction between detecting fragmented irregular lines and determining accurate line width.
Solution Approach 2:
The patent changes the parameter approach from direct line width measurement to statistical parameter estimation. Instead of measuring the width of each fragmented segment directly, the method collects width measurements from multiple clear segments and uses the mode (most frequent value) as the representative line width parameter. This statistical parameter transformation enables accurate width determination even when the line appears as separate segments due to irregularities.
2Manufacturing precision
If strict line continuity requirements are applied, then only well-drawn lines are recognized, but hand-drawn lines with natural irregularities are rejected or misidentified
Solution Approach 1:
The patent applies a dynamic approach to line recognition by adapting the detection criteria to the actual line quality. Instead of requiring continuous, uniform lines, the method dynamically identifies clear segments wherever they exist in the irregular line and uses statistical analysis to synthesize the overall line characteristics. This dynamic segmentation and statistical reconstruction enables the system to adapt to various degrees of line irregularity while maintaining recognition accuracy.
Solution Approach 2:
The patent converts the harmful effect of line irregularities (smudges, breaks, fades) into a beneficial statistical sampling process. Rather than viewing fragmented segments as errors to be corrected, the method treats them as natural occurrences and uses the clear segments as samples to determine the line's representative width through mode analysis. This transforms the problem of irregularity into an opportunity for robust statistical measurement that is actually more representative of hand-drawn lines.
Data Source
AI summary
A method for image processing includes obtaining a mask of a stroke from an image; determining a plurality of cross edges for the stroke based on the mask; generating a histogram comprising a plurality of widths of the cross edges and a plurality of frequencies of the plurality of widths from the cross edges; estimating a lower bound of a width range for the stroke based on a mode width of the plurality of widths, a first subset of the plurality of widths below the mode width, and a first plurality of weights assigned to the first subset of the plurality of widths; and estimating an upper bound of the width range for the stroke based on the mode width, a second subset of the plurality of widths above the mode width, and a second plurality of weights assigned to the second subset of the widths.