Image Forming Apparatus Halftone Screen Line Density Control
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Solution Overview
Problem
Existing image forming apparatuses face challenges in accurately controlling image density due to variations in detection values from sensors when using detection images subjected to screen processing with a low number of screen lines.
Innovation Solution
The apparatus performs halftone processing on detection images for tone correction and target maximum density correction, using a higher number of screen lines for detection images in maximum density correction to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If screen processing with a low number of screen lines is applied to detection images for image density control, then color reproducibility and tone reproducibility are improved, but detection value variation increases and image density control accuracy deteriorates
Solution Approach 1:
The patent segments the halftone processing into different types based on image attributes: screen processing with a first number of screen lines for text and line images, screen processing with a second number of screen lines for photo images, and error diffusion processing for graphic images. This segmentation allows each processing type to be optimized for its specific application, resolving the contradiction between detection accuracy and reproducibility by selecting the appropriate processing method for each image type.
Solution Approach 2:
The patent applies different halftone processing methods to different regions or types of images based on their attributes. Text and line images receive screen processing with a first number of screen lines optimized for shape reproducibility, while photo images receive screen processing with a second number of screen lines optimized for tone reproducibility. This local quality approach allows each image type to receive the processing quality it needs, resolving the detection accuracy issue without sacrificing overall system performance.
2Shape
If screen processing with a high number of screen lines is used for detection images, then shape reproducibility is improved, but color and tone reproducibility deteriorate
Solution Approach 1:
The patent divides the halftone processing into distinct categories based on image attributes, applying screen processing with a first number of screen lines specifically for text and line images where shape reproducibility is critical, and screen processing with a second number of screen lines for photo images where color and tone reproducibility are critical. This segmentation resolves the contradiction by matching the processing method to the image type requirements.
Solution Approach 2:
The patent implements local quality by applying different screen line densities to different image types. Text and line images receive high screen line density processing to maintain sharp shapes and lines, while photo images receive optimized screen line density processing to preserve color and tone accuracy. This localized optimization ensures that each image type receives the processing quality appropriate to its requirements.
3Measurement precision
If halftone processing is performed on detection images for maximum density correction, then image density control accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent segments the halftone processing into three distinct methods based on image attributes: screen processing with a first number of screen lines for text and line images, screen processing with a second number of screen lines for photo images, and error diffusion processing for graphic images. This segmentation simplifies the overall complexity by providing clear decision rules for selecting the appropriate processing method, making the system more manageable despite the multiple processing options.
Solution Approach 2:
The patent changes the processing parameters (number of screen lines, processing method) based on image attributes to optimize maximum density correction accuracy. By adjusting these parameters according to the specific image type, the system achieves high correction accuracy without requiring excessive processing complexity for all image types uniformly.
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 allows for the generation of image forming conditions that achieve a target maximum density with high accuracy, reducing variations in density control.
Implementation Method 1
a sensor configured to receive reflected light from the detection image
Data Source
AI summary
An image forming apparatus has an image processing unit that performs halftoning on image data and is controlled based on image forming conditions. The image forming unit forms an image based on image data on a sheet. A detection unit detects a detection image on the image carrier. A generation unit generates image forming conditions based on a detection result of the detection image. The image processing unit performs halftoning on the image data with a screen corresponding to attribute information of the image data, the screen including a first screen with a first number of screen lines and a second screen with a second number of screen lines greater than the first number of screen lines. The number of screen lines used for the detection image is greater than the number of lines of the first screen.