Vector Graphics Compression via Relative Absolute Command Selection
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Solution Overview
Problem
Existing technologies for compressing vector graphics are inefficient in reducing memory requirements while maintaining image quality, as they do not effectively utilize lossy compression methods to simplify or minify vector graphic data.
Innovation Solution
A computer-implemented method for compressing vector graphics that involves a simplification process and a minification process. The simplification process generates compressed shape commands by converting relative and absolute parameters, while the minification process determines whether shape commands define negligible lines or curves, and selectively records or omits them to reduce data size.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If lossy compression techniques are applied to reduce file size, then memory requirements are reduced, but image quality may deteriorate
Solution Approach 1:
The patent applies parameter changes by converting between absolute and relative coordinate systems, adjusting numerical precision, and transforming shape command parameters to achieve compression while maintaining visual fidelity. This resolves the contradiction by finding optimal parameter representations that reduce data size without perceptible quality loss.
Solution Approach 2:
The patent extracts and removes negligible geometric features (lines, curves, shapes) that do not contribute to the visual appearance of the graphic. By identifying and eliminating these redundant elements, the method reduces file size and memory requirements while preserving the essential visual quality of the image.
2Quantity of substance
If compression techniques are applied to reduce data size, then storage efficiency is improved, but processing complexity increases
Solution Approach 1:
The patent segments the vector graphic into individual shape commands and processes them independently through multiple passes. Each shape command is analyzed, transformed, and optimized separately, which manages processing complexity by breaking down the overall task into smaller, manageable units that can be handled systematically.
Solution Approach 2:
The patent applies partial action by selectively processing only those shape commands that will benefit from compression techniques, rather than uniformly processing all data. Negligible features are identified and removed without applying complex transformations, while significant features receive optimized processing, thus balancing compression effectiveness with processing complexity.
Data Source
AI summary
Described herein is a computer implemented method for compressing a shape. The method includes: receiving input shape data defining first and second original shape commands and generating first and second compressed shape commands corresponding thereto. Generating the second compressed shape command includes generating a relative shape command that is a version of the second original shape command in which parameters are relatively defined; generating an absolute shape command that is a version of the second original shape command in which parameters are absolutely defined; and selecting a smaller or equal smallest of the relative shape command and the absolute shape command to be the second compressed shape command.