Image Object Category-Based Filter Adjustment
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Solution Overview
Problem
Existing electronic devices struggle to select and apply suitable adjustment filters to multiple objects in an image, and lack a method to efficiently cancel adjustment filters applied to specific objects.
Innovation Solution
An electronic device and method for identifying categories of multiple objects in an image and applying adjustment filters corresponding to those categories, with the ability to apply or cancel these filters based on user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If adjustment filters are automatically applied to multiple objects based on category identification, then image adjustment efficiency is improved, but user control and flexibility are reduced
Solution Approach 1:
The system automatically identifies objects and applies appropriate adjustment filters based on category recognition, enabling the system to serve itself without requiring manual user intervention for each adjustment decision
Solution Approach 2:
The system provides dynamic user control mechanisms that allow users to modify, cancel, or adjust filter applications in real-time, transforming the static automatic process into a flexible interactive system that adapts to user needs
2Manufacturing precision
If multiple adjustment filters are applied to different objects in an image, then image quality and suitability are improved, but system complexity increases
Solution Approach 1:
The system divides the image into multiple object regions and applies different adjustment filters to each segment based on object category, allowing precise control over different parts of the image independently
Solution Approach 2:
Different adjustment filters are applied to different objects within the same image based on their specific categories and characteristics, ensuring that each object receives the appropriate local treatment rather than a uniform global adjustment
3Speed
If automatic category-based filter selection is implemented, then processing speed is improved, but adaptability to user preferences is reduced
Solution Approach 1:
The system performs preliminary category identification and filter selection automatically, but maintains the ability for users to override or adjust these preliminary decisions to match their specific preferences
Solution Approach 2:
The system incorporates user feedback mechanisms that allow users to indicate their preferences and adjust the automatic filter applications, creating a feedback loop that improves adaptability while maintaining processing efficiency
Data Source
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Figure 3A~3B
AI summary
An electronic device is disclosed, including a display, a camera, and at least one processor. The processor implements the method, including displaying a first preview image acquired through the camera on the display, identifying a category for each object included in the first preview image, applying adjustment filters to each object, each adjustment filter selected based on the identified category, display a second preview image on the display, in which each object is visually altered by the applied adjustment filters, displaying on the second preview image a plurality of selectable icons each corresponding to one of the identified categories, in response to receiving a first input selecting a first selectable icon, removing application of a first adjustment filter from a first object belonging to a category corresponding to the first selectable icon.