Dynamic Threshold Matrix Memory Allocation for Halftone Artifacts
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Solution Overview
Problem
Conventional image forming apparatuses face challenges in outputting color dots isotropically due to differences in characteristics between the conveyance and main scanning directions, leading to artifacts like crushed or interrupted halftone dots and non-uniform density, which are difficult to address with fixed memory allocations for threshold value matrices.
Innovation Solution
An image processing apparatus that dynamically allocates memory to threshold value matrices for each color based on image formation conditions, allowing flexible memory distribution and setting of matrix sizes to minimize visibility of artifacts, with the option to prioritize larger allocations for colors with higher visibility and set sizes as powers of 2, ensuring the total memory usage remains within a predetermined limit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If fixed memory allocation is used for threshold value matrices, then device complexity is reduced, but adaptability to different image formation conditions deteriorates
Solution Approach 1:
The patent implements dynamic memory allocation for threshold value matrices based on image formation conditions. The allocation amount is adjusted according to the number of colors and specific formation conditions, allowing the system to adapt flexibly without fixed constraints. This resolves the contradiction by making the memory allocation dynamic rather than static, improving adaptability while maintaining manageable complexity through automated adjustment.
2Manufacturing precision
If larger threshold value matrices are used, then manufacturing precision of halftone images is improved, but memory usage increases
Solution Approach 1:
The patent changes the parameter of threshold value matrix size dynamically based on image formation conditions. Instead of using a fixed large matrix for all cases, the system adjusts the matrix size parameter according to the number of colors and specific conditions, achieving high precision when needed while conserving memory when smaller matrices suffice. This resolves the contradiction by making matrix size a variable parameter rather than a fixed value.
Solution Approach 2:
The patent applies different threshold value matrix sizes to different colors based on their specific requirements. Each color can have an optimally sized matrix allocated according to its visibility characteristics and image formation conditions, rather than using a uniform size for all colors. This local optimization achieves high overall image quality while efficiently utilizing memory resources.
3Stability of the object's composition
If memory allocation is optimized for each color, then halftone image uniformity is improved, but device complexity increases
Solution Approach 1:
The patent adjusts the memory allocation parameter for each color based on visibility characteristics and image formation conditions. By changing the allocation parameter dynamically rather than using fixed equal allocation, the system achieves uniform halftone images across different colors while managing complexity through automated parameter adjustment based on measurable characteristics.
Data Source
AI summary
An image processing apparatus which sets threshold value matrices for performing screen processing using the threshold value matrices for respective pieces of image data for a plurality of colors according to an output image, the apparatus including: an allocation section which distributes and allocates memories to the respective threshold value matrices used for the respective pieces of the image data for the plurality of colors within a range that a total of memory allocation amounts to the threshold value matrices is equal to or less than a predetermined upper limit size; a setting section which sets the threshold value matrices in sizes according to the respective memory allocation amounts; and a storage section which stores the set plurality of threshold value matrices in respective allocated memory areas.