Selective Rasterization for High Fidelity Document Conversion
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Solution Overview
Problem
Existing document conversion technologies lose fidelity and increase document size by rasterizing entire documents to support unsupported vector data, limiting the usability of the converted document.
Innovation Solution
The method involves identifying bounding areas with unsupported vector data, rasterizing only those areas, and retaining vector data for non-rasterized elements, thereby creating a higher fidelity and more compact document by selectively converting blended elements to raster data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the entire document is rasterized to convert unsupported vector data, then compatibility with less rich formats is achieved, but document size increases and fidelity is lost
Solution Approach 1:
The document is divided into multiple regions: regions containing unsupported vector data are identified and rasterized, while regions with supported vector data are retained in their original vector format. This selective segmentation allows compatibility to be achieved only where necessary, preserving fidelity in other areas.
Solution Approach 2:
Different processing approaches are applied to different parts of the document based on local requirements. Areas with unsupported vector data receive rasterization treatment, while areas with supported data maintain vector quality. This local differentiation resolves the contradiction by applying compatibility measures only where needed rather than uniformly across the entire document.
2Adaptability or versatility
If the entire document is rasterized to convert unsupported vector data, then compatibility with less rich formats is achieved, but document size increases
Solution Approach 1:
The document is segmented into rasterized regions and vector regions. Only the necessary portions containing unsupported data are converted to raster format, while the remainder stays in compact vector format. This reduces the overall quantity of raster data and consequently reduces document size compared to full rasterization.
Solution Approach 2:
Rasterization is applied locally only to areas requiring compatibility, rather than globally to the entire document. This localized approach minimizes the increase in document size by converting only the minimum necessary portions to raster format.
3Loss of information
If vector data is retained in the converted document, then fidelity is preserved, but compatibility with less rich formats is reduced
Solution Approach 1:
The document is segmented into compatible and incompatible vector elements. Unsupported vector elements are isolated and rasterized, while supported vector elements are retained. This allows the document to maintain high fidelity for supported elements while achieving compatibility through selective rasterization of problematic elements.
Solution Approach 2:
Different data formats are applied locally to different elements based on their compatibility requirements. Supported vector data retains its high-fidelity vector format, while unsupported elements are converted to raster format for compatibility. This resolves the contradiction by allowing vector data retention where it benefits fidelity without sacrificing overall compatibility.
Data Source
AI summary
One or more techniques and/or systems are disclosed for high fidelity conversion of a document to a less rich format. A bounding area can be identified in the document that comprises an unsupported element, and/or a blending of elements that is not supported in the less rich format. The bounding area that comprises the unsupported element(s) can be rasterized, by creating an image and identifying raster data for the image. Those elements in the document that are outside the bounding area are not rasterized, and their vector data-based format is retained in the converted document.