Character Pixel Identification in Halftone Images
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Solution Overview
Problem
Existing image processing techniques fail to accurately identify character pixels in images containing halftone dots, often misidentifying pixels constituting halftone dots as character pixels.
Innovation Solution
An image processing apparatus and method that acquires target image data, determines candidate character pixels, sets object regions, and identifies character pixels by applying specific determination conditions to both individual pixels and object regions, ensuring accurate characterization of pixels as either character or non-character.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional edge determination and halftone dot determination are performed for each pixel, then character pixels can be identified, but pixels constituting halftone dots are misidentified as character pixels
Solution Approach 1:
The image is divided into multiple object regions, and candidate character pixels are determined differently for each region based on its characteristics. This segmentation allows the system to apply appropriate determination conditions to each region, reducing misidentification of halftone dots as character pixels while maintaining accurate character pixel identification.
Solution Approach 2:
Different determination conditions are applied to different object regions based on their local characteristics. The system determines candidate character pixels using first determination conditions for individual pixels and second determination conditions for object regions, allowing local adaptation to reduce halftone dot misidentification in specific regions while maintaining overall identification accuracy.
2Measurement precision
If multiple determination conditions are applied to identify character pixels, then identification accuracy improves, but processing complexity increases
Solution Approach 1:
The system performs preliminary determination of candidate character pixels for each pixel using first determination conditions before performing the second determination based on object regions. This preliminary action organizes the processing flow and allows subsequent steps to focus on region-specific verification, managing complexity through structured multi-stage processing.
Solution Approach 2:
The system performs determination processes at multiple levels (individual pixel level and object region level), applying more determination conditions than a simple per-pixel approach. This partial application of determination conditions at different levels ensures high identification accuracy while managing complexity through hierarchical processing.
Data Source
AI summary
In an image processing apparatus, a controller is configured to perform: acquiring target image data representing a target image including a plurality of pixels; determining a plurality of first candidate character pixels from among the plurality of pixels, determination of the plurality of first candidate character pixels being made for each of the plurality of pixels; setting a plurality of object regions in the target image; determining a plurality of second candidate character pixels from among the plurality of pixels, determination of the plurality of second candidate character pixels being made for each of the plurality of object regions according to a first determination condition; and identifying a character pixel from among the plurality of pixels, the character pixel being included in both the plurality of first candidate character pixels and the plurality of second candidate character pixels.