Paper Stain Detection via Pixel Extraction Compression
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Solution Overview
Problem
Conventional paper-sheet stain detection apparatuses require large memory and processing capacity to detect fine graffiti lines, leading to increased costs and circuit size due to the need for high-resolution image data, which is inefficient for detecting fine lines drawn with pencils or similar tools.
Innovation Solution
The apparatus compresses image data by extracting the lowest or brightest pixel values from each extraction target area, allowing for efficient detection of stains without enlarging the circuit size, using an irradiating unit, image obtaining unit, identification unit, area information storage, image compressing unit, and stain determining unit to process the compressed image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution image data is used to detect fine graffiti lines, then detection precision is improved, but memory capacity and circuit size increase
Solution Approach 1:
The patent extracts only the essential information needed for stain detection by compressing image data to retain minimum necessary resolution. Instead of processing complete high-resolution images, the system extracts key features and compresses the data, removing redundant information while preserving detection capability for fine graffiti lines.
Solution Approach 2:
The patent changes the resolution parameter of image data from high-resolution to a compressed lower resolution that is sufficient for detection purposes. By adjusting this parameter, the system reduces memory requirements while maintaining the ability to detect fine stains, achieving an optimal balance between detection precision and memory capacity.
2Measurement precision
If high-resolution image data is used to detect fine graffiti lines, then detection precision is improved, but circuit size increases
Solution Approach 1:
The patent extracts only the essential information needed for stain detection by compressing image data to retain minimum necessary resolution. Instead of processing complete high-resolution images, the system extracts key features and compresses the data, removing redundant information while preserving detection capability for fine graffiti lines.
Solution Approach 2:
The patent changes the resolution parameter of image data from high-resolution to a compressed lower resolution that is sufficient for detection purposes. By adjusting this parameter, the system reduces memory requirements while maintaining the ability to detect fine stains, achieving an optimal balance between detection precision and memory capacity.
3Productivity
If high processing speed is achieved by using a high-performance CPU, then productivity is improved, but cost and circuit size increase
Solution Approach 1:
The patent applies partial action by processing only the essential compressed image data rather than complete high-resolution images. This reduces the computational burden to a level that can be handled by standard CPUs without requiring high-performance processors, thereby maintaining productivity while reducing cost and circuit size.
Solution Approach 2:
The patent changes the data volume parameter by compressing image data before processing. This parameter change reduces the amount of data the CPU must handle, enabling faster processing with standard hardware and eliminating the need for expensive high-performance processors.
4Productivity
If high processing speed is achieved by using a high-performance CPU, then productivity is improved, but cost increases
Solution Approach 1:
The patent applies partial action by processing only the essential compressed image data rather than complete high-resolution images. This reduces the computational burden to a level that can be handled by standard CPUs without requiring high-performance processors, thereby maintaining productivity while reducing cost and circuit size.
Solution Approach 2:
The patent changes the data volume parameter by compressing image data before processing. This parameter change reduces the amount of data the CPU must handle, enabling faster processing with standard hardware and eliminating the need for expensive high-performance processors.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables the detection of fine graffiti lines with reduced memory and processing requirements, maintaining the characteristic of the fine lines while decreasing the storage capacity and calculation time, thus reducing the overall cost and size of the apparatus.
Implementation Method 1
a paper sheet which is being transported is irradiated with light from a light source, and reflected light or transmitted light thereof is received by a light receiving sensor
Data Source
AI summary
In an apparatus for detecting a stain on a paper-sheet, a type and a transportation direction of the paper sheet are identified, and the information on whether each extraction target area of a read image corresponds to a white portion or a patterned portion of the paper sheet are stored. When the extraction target area corresponds to the white portion, a pixel having a lowest pixel value is extracted from a plurality of pixels constituting the extraction target area, and the read image is compressed into the pixel values of the extracted pixels as representative values, to generate a compressed image including a characteristic of a fine graffiti line drawn with a pencil or the like.