Halftone Parameter Identification for Image Density Stabilization
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Solution Overview
Problem
Existing image forming technologies face challenges in stabilizing image quality due to variations in electric charge, temperature, humidity, and sensitivity of photosensitive materials, particularly when dealing with halftone-processed image data, as methods like controlling developing conditions or modifying image data using a Gamma Look-Up Table (γLUT) are ineffective.
Innovation Solution
The solution involves identifying the halftone process parameters applied to input image data, forming a patch image using these parameters, detecting the patch image density, and adjusting image forming conditions accordingly, enabling effective stabilization even with halftone-processed data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the method of modifying image data using γLUT is used, then control response is improved, but it becomes ineffective when halftone-processed image data is inputted
Solution Approach 1:
The invention changes the approach from modifying γLUT parameters to identifying halftone process parameters (such as screen frequency, screen angle, and halftone method) and applying corresponding corrections based on these identified parameters. This allows the system to adapt to halftone-processed data by detecting its characteristics and applying appropriate compensation.
Solution Approach 2:
The invention performs preliminary identification of halftone process parameters applied to the input image data before forming the patch image. By detecting the halftone characteristics in advance, the system can prepare appropriate correction strategies, making the control process effective even with pre-processed halftone data.
2Adaptability or versatility
If the method of controlling developing conditions is used, then adaptability to different conditions is improved, but control response becomes slow
Solution Approach 1:
The invention performs preliminary identification of halftone process parameters before patch image formation. By detecting the halftone characteristics in advance, the system can prepare appropriate correction strategies, enabling faster response while maintaining adaptability to different halftone processing conditions.
Solution Approach 2:
The invention uses feedback from the detected halftone process parameters to adjust the patch image formation and subsequent image forming conditions. The density detection result feeds back to refine the correction, creating a responsive control loop that adapts to different halftone inputs while maintaining fast response.
3Ease of manufacture
If patch image density detection is performed without considering halftone process parameters, then measurement simplicity is improved, but manufacturing precision deteriorates
Solution Approach 1:
The invention performs preliminary identification of halftone process parameters (screen frequency, screen angle, halftone method) before forming the patch image. This preliminary action ensures that the patch image is created with appropriate settings matching the input data's halftone characteristics, enabling accurate density detection without complicating the overall process.
Solution Approach 2:
The invention changes the patch image formation process by incorporating halftone process parameter identification. The system detects parameters such as screen frequency and screen angle, then uses these to generate a patch image that accurately reflects the halftone characteristics, improving density measurement precision while maintaining process simplicity.
Data Source
AI summary
An image forming apparatus appropriately adjusts an image forming conditions even if a halftone-processed image data is inputted. The image forming apparatus forms a patch image by applying a halftone process which is substantially equivalent to the halftone process which has been previously performed for the inputted image data. The image forming apparatus detects the density of the formed patch image and adjusts the image forming conditions according to the detected density.