Gradient Image Vectorization with Segmented Boundary Preservation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional vectorization systems face issues with computational accuracy, efficiency, and operational flexibility, leading to poor visual appearance and large file sizes due to excessive solid bands and reliance on user input.
Innovation Solution
A gradient image segmentation system that uses a segmentation model to minimize boundaries and apply gradient fill functions, along with constant or piecewise constant fills, to generate high-quality vectorized digital images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional vectorization systems use solid bands to represent image regions, then the vectorized image can be generated quickly, but the visual appearance deteriorates and file size increases
Solution Approach 1:
The patent changes the fill representation from solid bands to gradient fills by introducing gradient direction and gradient stops as new parameters. This allows smooth color transitions within regions while maintaining vector format efficiency, resolving the contradiction between fast generation and visual quality
Solution Approach 2:
The system dynamically selects between solid fills and gradient fills for different regions based on gradient detection results. Regions with significant color variations use gradient fills while uniform regions use solid fills, optimizing both visual quality and file size
2Quantity of substance
If conventional vectorization systems minimize the number of regions, then file size is reduced, but boundary accuracy deteriorates
Solution Approach 1:
The patent applies segmentation to divide the image into regions based on gradient characteristics rather than simple color clustering. This allows boundaries to align with actual image edges while keeping the number of regions manageable, maintaining both boundary accuracy and file size efficiency
Solution Approach 2:
The system applies different fill types (solid or gradient) to different regions based on local gradient characteristics. This local adaptation allows accurate boundary representation in complex areas while using simpler representations in uniform areas, optimizing the balance between accuracy and file size
3Adaptability or versatility
If conventional vectorization systems rely on user input for parameter adjustment, then operational flexibility is improved, but ease of operation deteriorates
Solution Approach 1:
The system performs automatic gradient detection and automatic selection of fill types for each region without requiring user input. The algorithm autonomously analyzes image gradients and determines the optimal representation method, eliminating the need for manual parameter adjustment while maintaining high-quality results
Data Source
AI summary
The present disclosure relates to systems, methods, and non-transitory computer-readable media that generates a vectorized digital image of a raster image according to at least one gradient fill function. In particular, the disclosed systems generate a segmentation map of a raster digital image by using a segmentation model to cluster pixel values while minimizing a number of boundaries. Moreover, the disclosed systems generate one or more closed connected partitions that include locally smooth pixel values within the raster digital image according to the boundaries of the segmentation map. Further, the disclosed systems fit one or more fill function to the closed connected partition(s), where the one or more fill function includes at least one gradient fill function for a closed connected partition. The disclosed systems generate the vectorized digital image according to the at least one gradient fill function for the closed connected partition.