Image Segmentation Using Multi-Mode Mask Selection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional methods for extracting image elements, such as foreground or background objects, are tedious and often produce undesirable results, especially when dealing with complex images or images with indistinguishable foreground and background.
Innovation Solution
A method that allows users to select image elements using multiple selection modes (text-based, point-based, and bounding shape-based) and combines these modes to generate precise extraction masks, utilizing machine learning tools for improved segmentation and edge refinement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional manual tracing methods are used to extract image elements, then extraction precision can be controlled by user skill, but the process becomes long and tedious, significantly reducing productivity
Solution Approach 1:
The patent segments the image extraction process into multiple selection modes (text-based, point-based, bounding shape-based) that can be independently applied and combined. Each mode handles specific aspects of selection, allowing the system to automatically generate multiple image masks that can be combined to create precise extraction masks, thereby achieving both high precision and improved productivity
Solution Approach 2:
The patent introduces machine learning-based segmentation tools as intermediaries between the user input and the final extraction mask. These tools automatically process user inputs (text, points, bounding shapes) to generate image masks, eliminating the need for manual tracing while maintaining precision through intelligent algorithms
2Productivity
If automatic selection tools and background removal methods are used, then productivity is improved, but the results are often undesirable due to inability to handle complex images with indistinguishable foreground and background
Solution Approach 1:
The patent implements a dynamic selection system where users can switch between different selection modes (text-based, point-based, bounding shape-based) depending on the image complexity. The system adapts its behavior based on the image content, allowing manual intervention when automatic methods fail and automated processing when images are straightforward, thus maintaining both speed and accuracy
Solution Approach 2:
The patent merges multiple selection modes and multiple image masks into a unified extraction mask through combination operations. By combining the results from different selection modes (text-based, point-based, bounding shape-based), the system achieves more accurate extraction of complex image elements than any single mode could achieve alone, while maintaining high productivity
3Adaptability or versatility
If multiple selection modes are implemented to handle diverse image elements, then adaptability is improved, but the system complexity increases
Solution Approach 1:
The patent creates a universal image processing system where a single platform can handle multiple selection modes (text-based, point-based, bounding shape-based) and multiple image masks through a unified architecture. The machine learning-based segmentation tool serves as a universal processor that can interpret different input types and generate appropriate masks, reducing the need for separate specialized systems for each selection mode
Data Source
AI summary
Described embodiments generally relate to a method for extracting a portion of an image. The method includes accessing an image for editing; receiving at least one user input related to the accessed image, the at least one user input corresponding to at least one image element of the accessed image; based on the at least one user input, generating at least one new image mask; receiving a user input corresponding to at least one selected image mask; and generating an extraction mask based on each of the at least one selected image masks, to allow the portion of the image defined by the extraction mask to be extracted.