Image Reading Apparatus Dust-Free Shading Correction
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Solution Overview
Problem
Existing image reading apparatuses face challenges in obtaining dust-free shading data due to dust on the shading sheet or reading sensor, leading to tone unevenness and streaks in images, especially when dust is not perfectly removed, and existing solutions are either costly or prone to tone jumps.
Innovation Solution
An image reading apparatus that includes a hardware processor to determine the presence of dust on the shading sheet or reading sensor, producing ideal initial white reference data by complementing first white data with second white data obtained through additional scans, and using this data for shading correction before reading an image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a mechanism of moving an image reading sensor and/or wiping dust off is implemented, then dust-free shading data can be obtained, but device complexity and cost increase significantly
Solution Approach 1:
The patent creates a copy of the shading data by scanning the shading sheet again after cleaning, then uses this copied data to replace dust-affected regions in the original shading data. This avoids the need for complex mechanical dust removal mechanisms while achieving dust-free shading data.
Solution Approach 2:
The patent performs a preliminary cleaning action on the shading sheet before obtaining shading data. By cleaning the shading sheet in advance and then scanning it to obtain fresh shading data, the system eliminates dust interference without requiring complex real-time dust removal mechanisms during the scanning process.
2Measurement precision
If dust-adhered pixel data is replaced with dustless shading data using average values from surrounding pixels, then dust-affected data can be corrected, but tone jumps may occur at the edges of dust-adhered pixels
Solution Approach 1:
The patent applies different correction strategies to different regions based on their characteristics. By identifying dust-affected pixels and applying localized replacement only to those specific pixels using corresponding dustless pixel data from the cleaned scan, rather than using average values from surrounding pixels, the system maintains local quality and avoids introducing tone jumps at edges.
Solution Approach 2:
The patent uses the copied shading data from the cleaned shading sheet as a template to replace dust-affected regions. This copying approach allows precise replacement of only the affected pixels with corresponding clean pixel values, maintaining tone uniformity while correcting dust interference.
3Reliability
If shading data is obtained by scanning the shading sheet multiple times, then dust influence can be minimized, but reading time increases
Solution Approach 1:
The patent performs cleaning of the shading sheet as a preliminary action before obtaining the shading data. By cleaning in advance and then obtaining the data in a single scan, the system minimizes total time compared to multiple sequential scans, while still achieving dust-free data.
Solution Approach 2:
The patent obtains a copy of the shading data from a cleaned shading sheet and uses this copy to replace dust-affected regions. This approach allows the system to minimize the number of actual data acquisition scans while still achieving dust-free results through the use of the cleaned copy.
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 production of dust-free shading data even with incomplete cleaning, eliminating tone jumps and streaks, and reducing the cost and complexity of dust management in image reading systems.
Implementation Method 1
a light source that emits light; a reference member that reflects the light emitted from the light source
Implementation Method 2
a reading sensor that reads the light converged by the light-receiving lens
Implementation Method 3
a light-receiving lens that converges the light reflected from the reference member
Data Source
AI summary
An image reading apparatus includes: a light source; a reference sheet that reflects light emitted from the light source; a light-receiving lens that converges the reflected light; a reading sensor that reads the light converged by the light-receiving lens; and a hardware processor that: based on first white data obtained when the reading sensor reads the reference sheet for the first time, determines whether the reference sheet or the reading sensor has dust; in response to determining that the reference sheet or the reading sensor has dust, produces ideal initial white reference data by complementing the first white data with second white data obtained when the reading sensor reads the reference sheet for the second and subsequent times; and with the ideal initial white reference data, complements third white data obtained when the reading sensor reads the reference sheet right before reading an image of a job.