Raster Image Processing Device with Dynamic Brush Scaling
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Solution Overview
Problem
Existing image-processing devices struggle to form patterns of arbitrary size suitable for different printing resolutions, often resulting in patterns being too small or large due to standardized brush data, especially with high-resolution image-forming devices.
Innovation Solution
An image-processing device with a raster operation unit, size modifying unit, and combination deriving unit that adjusts the size of pattern image data based on printing resolution, converting ROP codes to execute equivalent image processes using either brush or source bitmap data, ensuring patterns are rendered appropriately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If standardized brush data of fixed size is used for ROP processes, then the image process can be executed efficiently on any device, but the pattern size becomes unsuitable for high-resolution image-forming devices
Solution Approach 1:
The patent introduces a dynamic size modification mechanism that adjusts brush data dimensions based on the image-forming device's resolution capabilities. The system determines whether size modification is needed and applies appropriate scaling transformations, making the originally fixed-size brush data adaptable to different resolution requirements while maintaining processing efficiency through conditional execution.
Solution Approach 2:
The patent modifies the size parameter of brush data according to the printing resolution of the target device. By changing the dimensional parameters of the pattern image data based on device capabilities, the system ensures patterns are rendered at appropriate scales for both high-resolution and low-resolution devices without sacrificing processing efficiency.
2Manufacturing precision
If brush data is enlarged to suit high-resolution devices, then pattern size becomes appropriate, but processing complexity increases
Solution Approach 1:
The patent performs size determination and modification decisions in advance before the actual image formation process. By pre-assessing whether size modification is necessary and pre-processing the brush data accordingly, the system reduces complexity during the main processing phase while ensuring patterns are appropriately sized for the target device.
Solution Approach 2:
The system automatically determines whether size modification is needed based on device resolution characteristics and self-adjusts the brush data dimensions without requiring manual intervention. This self-service mechanism simplifies the overall process by eliminating the need for external complexity management while maintaining appropriate pattern sizes.
3Adaptability or versatility
If ROP processes are applied to arbitrary-sized source bitmap data, then patterns can be formed of any size, but the processing time increases
Solution Approach 1:
The patent applies different processing approaches based on the specific requirements of each brush data instance. Rather than uniformly processing all brush data with the same method, the system selectively applies size modification only when necessary, maintaining arbitrary size flexibility for patterns that don't require modification while optimizing processing time for those that do.
Data Source
AI summary
Image-processing device for ROP is disclosed. Upon receiving a ROP command, the image-processing device determines whether the size of the brush data is required to be modified through a size modifying operation, based on the printing resolution of the printing device. If the size modifying operation is necessary, the image-processing device performs a process to enlarge or reduce the brush data, depending on the printing resolution. The image-processing device converts the ROP code associated with the operational expression using brush data to a combination of ROP codes associated with operational expressions using the source bitmap, but not brush data. The image-processing device controls a ROP processor to perform the ROP processes corresponding to these ROP codes using the enlarged or reduced brush data as the source bitmap in order to implement a ROP process equivalent to the ROP code inputted with the ROP command.