Image Processing Apparatus Code Region Pixel Conversion
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Solution Overview
Problem
Existing image processing technologies face challenges in maintaining the quality of codes, such as barcodes, during number-of-pixels conversion, as they often generate unnecessary halftone data and alter the ratio of code elements, leading to decreased code quality due to non-integer magnification factors used in the conversion process.
Innovation Solution
An image processing apparatus that includes a code detector and a number-of-pixels converting unit, which detects codes in the image data and adjusts the number of pixels by integer factors for regions containing codes, while using non-integer factors for other regions, preventing halftone data generation and maintaining code quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If number-of-pixels conversion is performed using a non-integer factor on the entire image data, then the productivity and adaptability of the image processing are improved, but the manufacturing precision and quality of code regions deteriorate due to halftone data generation and element ratio variation
Solution Approach 1:
The image data is segmented into code regions and non-code regions based on detection results. Different number-of-pixels conversion factors are applied to each segment: integer factors are used for code regions to maintain precision, while non-integer factors are used for non-code regions to improve productivity and adaptability. This segmentation resolves the contradiction by allowing different processing strategies for different parts of the image.
Solution Approach 2:
The patent applies local quality by using different conversion factors in different regions of the image. Code regions receive integer-factor conversion to preserve quality, while non-code regions receive non-integer-factor conversion for better adaptability. This local differentiation allows the system to optimize for both precision and productivity in appropriate locations.
2Manufacturing precision
If number-of-pixels conversion is performed using an integer factor on code regions, then the manufacturing precision and code quality are maintained, but the adaptability to various output conditions is reduced
Solution Approach 1:
The image is segmented into code and non-code regions, allowing integer-factor conversion for code regions (maintaining precision) and non-integer-factor conversion for non-code regions (maintaining adaptability). This segmentation resolves the contradiction by applying different conversion strategies where appropriate.
Solution Approach 2:
Different conversion factors are applied locally: integer factors in code regions for quality preservation, and non-integer factors in non-code regions for output flexibility. This local quality approach allows the system to satisfy both precision and adaptability requirements simultaneously in different locations.
3Device complexity
If the entire image data is processed with uniform number-of-pixels conversion, then the device complexity is reduced, but the manufacturing precision of code regions deteriorates when non-integer factors are used
Solution Approach 1:
The patent introduces segmentation of the image into code and non-code regions, which increases processing complexity but is necessary to prevent code quality deterioration. The segmentation allows the system to apply appropriate conversion factors to each region, resolving the contradiction between simplicity and precision.
Solution Approach 2:
The patent applies local quality by using different conversion factors for different regions. This increases device complexity compared to uniform processing, but is necessary to maintain code quality in regions where precision is critical while allowing flexibility in other regions.
Data Source
AI summary
An image processing apparatus includes: a code detector configured to detect a code included in image data, and a number-of-pixels converting unit configured to increase the number of pixels of the image data by converting the number of pixels of the image data by a factor of N, wherein, when N is a non-integer, the number-of-pixels converting unit converts the number of pixels in a first region including the code in the image data by an integer factor and converts the number of pixels in a second region different from the first region in the image data by a factor of N.