Image Reading Device Abnormality Detection via Temperature Compensation
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Solution Overview
Problem
Existing image reading devices face challenges in accurately detecting abnormalities such as fingerprints or dust on the document surface due to variations in light source intensity and temperature, leading to erroneous identification of clean areas as dirty.
Innovation Solution
An image reading device that includes a reading unit, a control unit, and a storage unit, where the control unit determines abnormalities by comparing read values from a document sheet with standard data and temperature variation data stored in the storage unit, using calculated values based on twice the standard deviations of temperature-induced variations to differentiate between actual dirt and temperature-induced changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If temperature compensation based on standard deviation is implemented, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system performs preliminary temperature compensation by storing standard deviation data obtained under various temperature conditions. When detecting abnormalities, the system retrieves and applies the appropriate standard deviation threshold based on current temperature, rather than calculating it in real-time. This preliminary preparation reduces computational complexity during actual operation while maintaining high detection precision.
Solution Approach 2:
The system uses its own historical data (standard deviations obtained during normal operation) to establish detection thresholds. By utilizing internally collected temperature-varied data to compensate for temperature effects, the system achieves self-service compensation without requiring external calibration equipment or complex external systems.
2Device complexity
If simple ratio-based dirt detection is used, then device complexity is reduced, but reliability deteriorates due to erroneous detection
Solution Approach 1:
The system changes the detection parameter from a simple ratio comparison to a statistically-based threshold comparison using standard deviations. By incorporating temperature as a variable parameter and using standard deviation thresholds to account for temperature-induced variations, the system maintains algorithmic simplicity while significantly improving detection reliability and reducing false positives.
Data Source
AI summary
An image reading device includes a reading unit that reads a document sheet and a reading standard surface and outputs read values corresponding to pixels arranged in a main scan direction, a control unit that processes the read values, and a storage unit storing information to be referenced by the control unit. In the storage unit, first data that is read values of the reading standard surface and serves as standards, and second data on ranges of variation, based on a change in a temperature, in the read values are stored. The control unit determines, based on the first data and the second data read from the storage unit and third data obtained by reading the reading standard surface after an acquisition of the first data, whether an abnormality exists in the pixels.