Document Scanning Resolution Segmentation
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Solution Overview
Problem
Current scanners use a fixed scan resolution for all document pages, leading to inefficient file sizes and image quality, as higher resolutions are wasted on empty spaces, and lower resolutions degrade image quality, especially in varying content documents.
Innovation Solution
Segmenting scanned images into regions of interest to determine the minimum scanning resolution for each area, using feature maps and machine learning to classify pixels and optimize resolutions for text, non-text, and background areas, ensuring readability and clarity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed high scan resolution is used for all document pages, then image quality is maintained, but file size increases and memory is wasted on empty spaces
Solution Approach 1:
The document page is segmented into multiple content areas (text regions, image regions, blank regions) based on analysis of the document structure. Each content area is then assigned an appropriate scan resolution based on its specific requirements, rather than applying a uniform high resolution to the entire page. This segmentation allows high resolution to be applied only where necessary for maintaining image quality.
Solution Approach 2:
Different scan resolutions are applied to different content areas within the same document page. Text regions receive one resolution, image regions receive another, and blank regions receive a lower resolution or are skipped entirely. This local quality approach ensures that image quality is maintained in critical areas while reducing overall file size by avoiding unnecessary high-resolution scanning in less critical areas.
2Quantity of substance
If a fixed low scan resolution is used for all document pages, then file size is reduced, but image quality degrades in areas requiring higher detail
Solution Approach 1:
The document is divided into content areas with different quality requirements. By segmenting the document, the system can apply low resolution to blank or less critical areas while reserving high resolution for text and image regions where quality is essential. This selective approach maintains overall image quality while reducing the total file size compared to uniform high-resolution scanning.
Solution Approach 2:
The scanning system applies different resolution qualities to different local regions of the document based on content type. Critical regions (text, images) receive high resolution to maintain quality, while non-critical regions (margins, blank spaces) receive low resolution or are excluded from scanning. This local quality differentiation resolves the contradiction by ensuring quality where needed while minimizing file size overall.
3Device complexity
If uniform scan resolution is applied to all content areas, then processing is simplified, but efficiency decreases due to memory waste on empty spaces
Solution Approach 1:
The document scanning process is segmented into distinct phases: first, the document is analyzed to identify content areas and their types; second, appropriate scan resolutions are assigned to each content area; third, scanning is performed with the optimized resolution for each region. While this adds analytical steps, it eliminates the waste of scanning entire pages at high resolution, thereby improving overall scanning efficiency and reducing memory usage.
Solution Approach 2:
Before the actual scanning process, the system performs preliminary analysis of the document to identify content areas, their types, and appropriate resolution requirements. This preliminary action of document analysis and resolution planning enables the subsequent scanning phase to be highly efficient, avoiding the memory waste that would occur with uniform high-resolution scanning of entire pages including blank spaces.
Data Source
AI summary
Examples disclosed herein relate to identifying a plurality of content areas of a document to be scanned, classifying each of the plurality of content areas into a content type, determining a minimum scanning resolution to maintain readability for each of the plurality of content areas according to the classified content type, and performing a scan of the document to a digital file, wherein each of the plurality of content areas is scanned at least at the determined minimum scanning resolution to maintain readability of the respective content area.