Image Processing Apparatus Halftone-Dot Region Determination
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Solution Overview
Problem
Conventional image processing apparatuses incorrectly determine halftone-dot regions as character regions, leading to deterioration in image quality due to erroneous smoothing of character features, especially in small-sized characters and Japanese characters, where isolated points are misidentified.
Innovation Solution
An image processing apparatus that divides image data into large and small blocks, calculates the number of isolated points in each block, and uses a halftone-dot region determination unit to accurately distinguish between halftone-dot and character regions by considering both block and sub-block isolated point counts, ensuring appropriate processing for each area.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If smoothing is applied to regions determined to be halftone-dot regions, then moiré phenomenon is prevented, but character sharpness deteriorates due to erroneous determination of character regions as halftone-dot regions
Solution Approach 1:
The image data is divided into blocks of a prescribed size, and each block is further divided into multiple sub-blocks. The determination of halftone-dot regions is performed by analyzing isolated points at both the block level and sub-block level, rather than treating the entire block uniformly. This segmentation allows for more precise local characterization of image regions.
Solution Approach 2:
The patent applies different processing approaches to different regions within blocks. By evaluating isolated point distribution at the sub-block level, the system can identify whether a block contains concentrated isolated points (character region) or evenly distributed isolated points (halftone-dot region), and apply smoothing only to appropriate halftone-dot regions while preserving character regions.
2Measurement precision
If isolated points are used to determine halftone-dot regions, then halftone-dot regions can be identified, but character regions with isolated points (such as small characters or Japanese characters) are incorrectly identified as halftone-dot regions
Solution Approach 1:
Each block is divided into multiple sub-blocks, and the isolated point distribution is analyzed at the sub-block level. This allows the system to detect whether isolated points are concentrated in specific sub-blocks (indicating character regions) or evenly distributed throughout the block (indicating halftone-dot regions), thereby improving determination reliability.
Solution Approach 2:
The patent introduces a new dimension of analysis by examining not only the total number of isolated points in a block but also the distribution pattern across multiple sub-blocks. This multi-level analysis (block level + sub-block level) provides additional information that helps distinguish between character regions and halftone-dot regions.
Data Source
AI summary
In the image processing apparatus, image data is divided into large blocks of a prescribed size and the large blocks are subdivided into small blocks by the dividing unit. The number of isolated points in each large block is then calculated by the large block isolated point calculation unit, and the number of isolated points in each small block is then calculated by the small block isolated point calculation units. It is then determined by the halftone-dot region determination unit whether or not the large block is a halftone-dot region. This determination considers both the number of isolated points in the large block and the number of isolated points in each small block.