Coherent Selection Mask for Image Editing
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Solution Overview
Problem
Current image editing tools require a tedious and inaccurate two-step process for making local adjustments to digital images, involving selection and application of adjustments, with existing technologies often failing to provide efficient segmentation and accurate object selection.
Innovation Solution
The system enables a user to perform segmentation and selection of digital data with a 'brush tool' that automatically generates a coherent selection mask, allowing for live, interactive adjustments and near real-time feedback, with the ability to modify parameters and create new adjustments seamlessly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated selection mask definition is implemented, then productivity is improved, but measurement precision deteriorates due to inaccurate object selection
Solution Approach 1:
The system provides real-time visual feedback during the brushing process, allowing users to see the selection mask being created and adjust their brushing accordingly. This feedback loop enables users to achieve accurate selections more quickly without requiring multiple undo/redo cycles, thus improving both productivity and selection precision simultaneously
Solution Approach 2:
The selection mask is created dynamically through the brushing process rather than being static. The mask evolves as the user brushes, allowing for flexible adjustment and refinement of the selection boundaries in real-time, which improves both the speed and accuracy of object selection
2Measurement precision
If manual selection process is used, then selection accuracy is improved, but loss of time increases due to tedious two-step process
Solution Approach 1:
The system merges the selection creation and adjustment application steps into a single integrated process. Users can apply adjustments directly to the selection as it is being created through brushing, eliminating the need for separate selection and adjustment steps, thus reducing time loss while maintaining accuracy
Solution Approach 2:
The system performs preliminary selection work automatically through the brushing process, pre-defining the selection mask and its boundaries before the user finalizes the adjustment parameters. This preliminary action reduces the overall time required by eliminating redundant manual selection steps
3Ease of operation
If brush tool with parametric control is used, then ease of operation is improved, but device complexity increases due to multiple parameters
Solution Approach 1:
The system provides self-service through automatic parameter adjustment based on the brushing context. The brush tool automatically adapts its parameters (such as size, shape, and intensity) based on the image content and brushing motion, reducing the cognitive load on users and simplifying operation while maintaining control flexibility
Solution Approach 2:
The system dynamically changes brush parameters based on the brushing context and user interactions. Parameters such as brush size, hardness, and flow are automatically adjusted during the brushing process to match the local image characteristics, providing intuitive control without requiring users to manually manage multiple parameters
4Manufacturing precision
If fixed image modification is applied, then manufacturing precision is improved, but adaptability deteriorates as parameters cannot be changed
Solution Approach 1:
The image modification is made dynamic and reversible. Users can adjust modification parameters (such as intensity, range, and type of adjustment) even after the initial application, and the system will recalculate and reapply the adjustment with the new parameters. This dynamic capability maintains precision while providing full adaptability
Solution Approach 2:
The system performs a preliminary modification with default parameters that can be adjusted later. This preliminary action establishes a baseline that can be refined without starting over, allowing users to maintain the accuracy of the initial modification while adapting parameters as needed
Data Source
AI summary
A method includes receiving a selection input to define a selection mask with respect to digital data. The selection input is used to generate the selection mask with respect to the digital data. An icon is automatically associated with the selection mask, the icon being selectable to select the selection mask.