Mark Sheet Image Processing for Partial Fill Detection
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Solution Overview
Problem
Conventional image processing systems struggle to accurately identify filled-in frames in mark sheets, especially when only a thin line or partial marks are present, leading to incorrect determination of frame fill status.
Innovation Solution
The image processing system generates a first image by removing boundary elements and a second image by removing small elements, identifies blank frames, and determines filled-in frames by identifying frames without corresponding blank frames within a specific distance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the conventional density-based method is used to determine frame fill status, then the system can process images quickly with simple calculations, but it fails to accurately identify frames with partial or thin line fills
Solution Approach 1:
The patent segments the frame identification process into distinct stages: extracting frame candidate regions from the image, calculating density values for these regions, and applying threshold-based classification. This segmentation allows the system to focus computational resources on relevant areas and improve accuracy without proportionally increasing overall complexity.
Solution Approach 2:
The patent introduces an intermediary density calculation step that processes frame candidate regions before final classification. By calculating average density values as an intermediate metric and comparing them against thresholds, the system bridges the gap between raw pixel data and fill status determination, improving accuracy while maintaining manageable complexity.
2Reliability
If the system uses maximum density value within the frame, then processing is simple and fast, but it produces incorrect results when large areas are unfilled
Solution Approach 1:
The patent changes the parameter used for fill determination from maximum density value to average density value within the frame. This parameter change fundamentally improves reliability by considering the overall fill status rather than being influenced by localized high-density regions, while the computational complexity remains comparable since both are statistical measures.
Solution Approach 2:
The patent replaces the mechanical approach of taking maximum density values with a more sophisticated density distribution analysis. By substituting the simple max operation with average density calculation and threshold comparison, the system achieves more reliable results without requiring complex mechanical or physical measurement systems.
3Measurement precision
If the system calculates average density of each pixel row and uses maximum value, then the algorithm is straightforward, but it cannot properly identify frames with thin line segments or check marks
Solution Approach 1:
The patent applies partial action by calculating density values only for frame candidate regions rather than processing the entire image. This selective approach improves precision for partial fill detection by concentrating computational effort on relevant areas, while the density calculation methodology itself remains relatively simple and straightforward.
Solution Approach 2:
The patent creates a simplified representation of frame regions through density calculation, effectively copying the essential fill information into a processed form that can be easily classified. This copying approach allows accurate detection of partial fills including thin lines and check marks without requiring complex analysis of the original pixel data.
Data Source
AI summary
An image processing system generates a first image by removing elements in contact with a boundary of a mark sheet area image from the mark sheet area image; generates a second image by removing from the first image elements whose area is equal to or smaller than a specific ratio (less than 1) of an area of an element having the largest area in the first image; identifies an element in the second image whose inside is not filled in as a blank frame; identifies, of elements within the mark sheet area image, an element whose position in a direction in which the frames are aligned with respect to the character string that represents an item is within a specific distance from the blank frame as a frame, and identifies a frame that has no corresponding blank frame as a filled-in frame, whose inside is filled in.