Selective Raster-to-Vector Edge Transformation
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Solution Overview
Problem
Conventional systems for converting raster images to vector drawings are inefficient and inaccurate, requiring significant user interaction, processing power, and time, often resulting in unsatisfactory results and wasteful resource usage.
Innovation Solution
A selective raster image transformation system that generates edge maps and selectively transforms user-selected edges of raster images into vector drawing segments using a pixel line stepping algorithm, reducing the number of user interactions and processing resources needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional batch conversion process is used to convert all edges in raster image to vector curves, then complete conversion is achieved, but significant user input time and processing resources are wasted
Solution Approach 1:
The patent extracts and processes only the necessary edge portions of the raster image that the user actually selects, rather than converting all edges. This is achieved by implementing a selective conversion mechanism where users can interactively choose specific regions or edges to convert, and the system processes only those selected portions into vector curves, thereby eliminating waste of time and resources on unnecessary conversions.
Solution Approach 2:
The patent applies partial action by converting only the portion of the raster image that the user deems necessary, rather than performing complete batch conversion. The system allows users to select specific edges or regions and converts only those selected portions, avoiding the excessive processing of entire images when only small portions are needed.
2Manufacturing precision
If manual digital tracing is used to convert raster image to vector drawing, then user control is maintained, but the process is tedious and time-consuming
Solution Approach 1:
The patent applies preliminary action by automatically detecting and preparing edge data from the raster image before user interaction. The system pre-processes the raster image to identify potential edges and creates a structured representation that is ready for user selection, eliminating the need for users to manually trace from scratch and significantly reducing tracing time while maintaining accuracy.
Solution Approach 2:
The patent introduces an intermediary automated edge detection and processing system that bridges the gap between raw raster images and final vector drawings. This intermediary layer automatically identifies edges, creates preliminary vector representations, and presents them to users for selection and refinement, combining automated efficiency with user control.
3Reliability
If conventional systems process entire raster images, then complete conversion is achieved, but computing devices waste unnecessary processing power and memory resources
Solution Approach 1:
The patent segments the raster image processing into distinct selectable portions rather than processing the entire image as a single unit. Users can divide the image into regions of interest and process only those segments, allowing the system to allocate processing power and memory resources efficiently to only the necessary portions of the image.
Solution Approach 2:
The patent applies partial action by processing only the selected portions of the raster image rather than the entire image. This selective processing approach ensures that computing resources are not wasted on converting edges or regions that the user does not need, while still achieving complete conversion of the necessary portions.
4Manufacturing precision
If high-resolution raster images are converted using conventional methods, then detailed results are achieved, but portable computing devices are incapable of handling the conversion
Solution Approach 1:
The patent segments high-resolution raster image processing into manageable portions that can be handled by portable devices. By allowing users to select and process only specific regions or edges rather than the entire high-resolution image, the computational complexity is reduced to levels that portable devices can handle while still maintaining detailed results for the selected portions.
Solution Approach 2:
The patent applies local quality by concentrating processing resources on achieving high detail and precision only in the selected regions of interest rather than attempting to process the entire high-resolution image. This allows portable devices to deliver detailed results for specific areas without requiring the full processing power needed for complete image conversion.
Data Source
AI summary
The present disclosure describes one or more embodiments of a selective raster image transformation system that quickly and efficiently generates enhanced digital images by selectively transforming edges in raster images to vector drawing segments. In particular, the selective raster image transformation system efficiently utilizes a content-aware, selective approach to identify, display, and transform selected edges of a raster image to a vector drawing segment based on sparse user interactions. In addition, the selective raster image transformation system employs a prioritized pixel line stepping algorithm to generate and provide pixel lines for selective edges of a raster image in real time, even on portable client devices.