Image Processing Apparatus Noise Symbol Differentiation
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Solution Overview
Problem
Existing image processing technologies fail to accurately distinguish between noise and small symbol elements in images, leading to partial removal of symbols during noise removal processes.
Innovation Solution
An image processing apparatus that includes a noise detecting unit, a comparative image retrieving unit, and a removing unit, which compares detected noise regions with comparative images to differentiate between noise and small symbol elements, ensuring only noise is removed from the image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If noise removal processing is performed on images including symbols, then noise is removed from the image, but small symbol elements are erroneously removed along with the noise
Solution Approach 1:
The patent segments the image processing into distinct functional units: a symbol detecting unit that identifies symbol elements, a noise detecting unit that detects noise regions, and a removing unit that selectively removes noise while preserving symbols. This segmentation allows independent optimization of each detection task and prevents erroneous removal of symbols by maintaining separate detection mechanisms for symbols and noise.
Solution Approach 2:
The patent introduces an intermediary classification mechanism that acts as a mediator between noise detection and removal. The classification unit determines whether detected regions are noise or symbol elements before removal, preventing direct removal of detected regions without verification. This intermediary step resolves the contradiction by adding a decision layer that preserves symbols while removing noise.
2Productivity
If noise detection sensitivity is increased to remove more noise, then noise removal effectiveness improves, but more symbol elements are incorrectly identified as noise
Solution Approach 1:
The patent applies local quality by using different detection criteria and parameters for different regions and types of features in the image. The symbol detecting unit and noise detecting unit use distinct detection strategies optimized for their respective targets, allowing high sensitivity for noise detection in certain areas while maintaining symbol preservation in other areas through localized decision-making.
Solution Approach 2:
The patent changes detection parameters dynamically based on image content and region characteristics. By adjusting detection thresholds, sensitivity levels, and classification criteria according to local image properties, the system achieves high noise removal efficiency in noise-prone regions while maintaining high precision in symbol-rich regions, resolving the contradiction between productivity and measurement precision.
Data Source
AI summary
An image processing apparatus includes an image retrieving unit that retrieves an image including a symbol, a noise detecting unit that detects noise of the image, a comparative image retrieving unit that retrieves a comparative image that is to be compared with a detection region of the image detected as the noise by the noise detecting unit, and a removing unit that, in accordance with comparison results of the detection region with the comparative image, removes from the image one portion of the detection region excluding the other portion of the detection region where at least part of the symbol included in the image is detected as the noise.