Print Data Scaling via Regions of Interest
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Solution Overview
Problem
Existing printing technologies face challenges in optimizing print output for various types of digital media, as print data is often not formatted for the specified media size, leading to inconsistent and suboptimal print results across different printers and devices.
Innovation Solution
A system that identifies and utilizes regions of interest within print data, such as art box, crop box, and media box, to scale and rotate the data according to the specified media size, following a precedence order to ensure standardized and optimal print output, using metadata from formats like PDF, PostScript, and SVG documents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If print data is printed without formatting for media size, then printing process is simple, but print output consistency deteriorates
Solution Approach 1:
The system performs preliminary actions by obtaining regions of interest from print data metadata before the actual printing process. This preprocessing step identifies important content areas and prepares scaling information in advance, allowing the printing system to automatically adapt print data to different media sizes without requiring manual intervention or complex formatting procedures.
Solution Approach 2:
The system changes parameters by dynamically determining scaling factors based on the identified regions of interest and the target media size. The scaling operation adjusts the dimensions and position of print content parameters to fit the specified media, enabling consistent print output across different media sizes while maintaining the simplicity of the printing process.
2Productivity
If print data is scaled without using regions of interest, then processing is faster, but print quality deteriorates
Solution Approach 1:
The system applies local quality by focusing scaling operations on specific regions of interest within the print data rather than uniformly processing the entire document. By identifying important content areas through metadata and applying scaling transformations selectively to these regions, the system maintains high print quality for critical content while avoiding unnecessary processing of other areas, thus balancing quality and efficiency.
3Productivity
If multiple regions of interest are processed in parallel, then scaling efficiency is improved, but system complexity increases
Solution Approach 1:
The system segments the print data processing by dividing it into distinct regions of interest identified through metadata. Each region can be processed independently according to its specific scaling requirements, allowing for efficient parallel or sequential processing without requiring complex coordination between different parts of the system. This segmentation approach improves scaling efficiency while keeping the system architecture relatively simple.
Data Source
AI summary
The disclosed embodiments provide a system that performs a print job. During operation, the system obtains one or more regions of interest associated with print data for the print job, wherein the print data is not formatted for a media size for the print job. Next, the system scales the print data based on a region of interest from the one or more regions of interest and the media size. Finally, the system sends the print job to a printer, wherein the print job is executed using the printer.