Image Noise Prediction via Multi-Sheet Density Integration
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Solution Overview
Problem
Conventional noise detection methods in image forming apparatuses struggle to predict latent noise occurrences on printed sheets, as they rely solely on test images and fail to detect invisible noise until it becomes visible on later printed sheets during continuous operations.
Innovation Solution
An image forming apparatus and method that integrates density values from non-image areas across multiple printed sheets using a sensor section that irradiates sheets with light in a specific direction, allowing for the prediction of noise occurrence based on integrated density values, enabling early detection of latent noise before it becomes visible.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional noise detection methods using test images are used, then the detection process is simple, but latent noise cannot be predicted until it becomes visible on later printed sheets
Solution Approach 1:
The system performs preliminary density measurements on non-image areas of printed sheets before noise becomes visible. By integrating density values from multiple sheets in advance, the system predicts latent noise occurrence proactively, rather than detecting it only after it becomes apparent on later sheets.
Solution Approach 2:
The system transitions from evaluating single-sheet test images to integrating density information across multiple sheets (M sheets) in the sheet feeding direction. This dimensional expansion from 2D test image analysis to 3D multi-sheet density integration enables detection of latent noise patterns that manifest over time.
2Reliability
If density integration across multiple sheets is performed, then latent noise prediction capability is improved, but processing time and computational load increase
Solution Approach 1:
The system extracts only the necessary density information from non-image areas of printed sheets, specifically line portions in the sheet feeding direction, rather than processing entire sheet images. This selective extraction reduces computational load while maintaining noise prediction accuracy.
Solution Approach 2:
The system performs partial integration by focusing only on specific line portions within non-image areas rather than integrating all pixels across multiple sheets. This partial action approach provides sufficient noise prediction capability with reduced processing requirements compared to complete sheet-wide integration.
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
The solution allows for the prediction of noise occurrence before it becomes visible on printed sheets, enhancing the ability to detect and prevent latent stripe noise, improving the reliability of noise detection during continuous printing operations.
Implementation Method 1
a sensor section which the printed sheets fed from the image forming section pass through or by in a first direction one by one, configured to irradiate each of the passing printed sheets with light elongated in a second direction different from the first direction, thereby sensing densities of the each of passing printed sheets
Data Source
Figure 1A
Figure 1B
Figure 2
AI summary
In an image forming apparatus 1, a sensor section 5 which the printed sheets fed from an image forming section 3 pass through or by in a first direction one by one, irradiates each of the passing printed sheets with light elongated in a second direction, thereby sensing densities of the each of passing printed sheets, on a pixel basis. Further, a control section 7 integrates densities of respectively corresponding line portions in respective non-image areas of sheets of the printed sheets, based on the densities obtained by the sensor section 5, each of the line portion extending substantially in the first direction and including pixels on substantially a same position in the second direction, thereby obtaining integrated density values, and predicts, based on the obtained integrated density values, that a noise will occur on a printed sheet to be made by the image forming section 1 later on.