Compact Digital Image Representation via Segmentation
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Solution Overview
Problem
Current image segmentation methods for digital images, particularly in document analysis, face challenges such as loss of information in binary conversion, complexity in color segmentation, and inefficiencies in processing and accuracy due to reliance on binary hierarchies and unreliable text classification techniques.
Innovation Solution
A method involving the segmentation of digital images into connected components in a one-pass manner, using block-based processing to estimate representative colors, quantify, and merge components, while storing statistics for noise removal and efficient compression, and employing layout analysis to partition images into foreground and background for compact representation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If binary thresholding is used for segmentation, then processing speed is improved, but information loss occurs in complex color documents
Solution Approach 1:
The patent segments the image processing task into multiple passes: first performing binary thresholding for quick initial segmentation, then performing color-based segmentation on the segmented regions to recover color information. This multi-level segmentation approach resolves the contradiction by applying different processing strategies to different aspects of the image.
Solution Approach 2:
The patent performs preliminary binary thresholding segmentation to identify candidate regions before performing more sophisticated color analysis. This preliminary action allows the system to quickly eliminate large portions of the image that don't require detailed color processing, while still preserving color information where needed.
2Manufacturing precision
If color segmentation is performed to preserve document structure, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The patent divides the color segmentation process into hierarchical levels: first segmenting into foreground and background using binary thresholding, then performing color-based segmentation only on the foreground regions. This reduces the overall complexity compared to full-image color segmentation while maintaining accuracy for document structures.
Solution Approach 2:
The patent applies different processing quality levels to different regions: simple binary thresholding for background regions and full color segmentation for foreground regions containing document content. This local differentiation maintains segmentation accuracy where needed while reducing complexity in less critical areas.
3Manufacturing precision
If multi-pass segmentation algorithms are used, then segmentation quality is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary binary thresholding to identify candidate regions before performing color-based segmentation. This preliminary action creates a focused search space for the more time-consuming color analysis, reducing overall processing time while maintaining segmentation quality.
Solution Approach 2:
The patent performs color segmentation only on regions identified as foreground by the binary thresholding, rather than processing the entire image with full color analysis. This partial action approach maintains segmentation quality for document content while significantly reducing processing time by skipping background regions.
4Measurement precision
If connected components are stored in detailed form, then measurement precision is improved, but memory usage increases
Solution Approach 1:
The patent extracts and stores only the essential statistics of connected components (such as bounding box, area, color properties) rather than storing complete pixel data for each component. This extraction approach maintains measurement precision for layout analysis while significantly reducing memory requirements.
Solution Approach 2:
The patent stores detailed component information only for foreground connected components that contain document content, while using simplified representations for background regions. This partial detail approach maintains precision where needed while reducing overall memory usage.
Data Source
AI summary
A method (100), an apparatus, and a computer program product for automatically producing a compact representation of a colour document are disclosed. In the method, a digital image of a colour-document page is segmented (110) into connected components in one-pass, block raster order. The digital image of the page is partitioned into foreground and background images using layout analysis (120) based on compact, connected-component statistics of the whole page. At least one portion of the background image where at least one portion of the foreground image obscures the background image is inpainting (520) in one-pass block raster order. The foreground and background images are combined (130) to form a compact document. A method, an apparatus, and a computer program product for segmenting a digital image comprising a plurality of pixels are also disclosed.