Material-Grouped Image Color Mapping for Multi-Layer Graphics
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Solution Overview
Problem
Current image processing methods for multi-element and multi-layer images, such as posters, suffer from low efficiency and poor color matching effects when manually adjusting colors.
Innovation Solution
An image processing method that groups target materials based on material attributes, determines a mapping relationship between the groups and candidate colors, and updates colors of the materials using a target color card to enhance color matching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual color selection and updating is used for multi-element and multi-layer images, then color matching adjustment can be performed, but processing efficiency is low and color matching effect is poor
Solution Approach 1:
The patent segments the image into multiple layers (background layer, object layer, material layer, text layer) and further divides the material layer into multiple material groups based on material attributes. This segmentation allows automated color mapping to be applied to specific groups of materials, improving processing efficiency while maintaining color matching accuracy for different material types.
Solution Approach 2:
The patent implements automated color mapping where the system automatically determines the target color for each material group based on the selected color option and updates the colors of target materials without requiring manual selection for each material. This self-service approach significantly improves processing efficiency while maintaining good color matching effects.
2Productivity
If automated color mapping is implemented, then processing efficiency improves, but complexity of the system increases
Solution Approach 1:
The patent segments materials into groups based on their attributes (such as material type, texture, or visual characteristics) and pre-establishes mapping relationships between these groups and color options. This segmentation strategy simplifies the automated mapping process by reducing the complexity of one-to-many material color mappings to more manageable group-level mappings.
Solution Approach 2:
The patent performs preliminary actions by pre-categorizing materials into groups and pre-establishing mapping relationships between material groups and color options before the actual color mapping operation. This preliminary organization reduces the computational complexity during automated color mapping by avoiding the need to evaluate all possible material-color combinations in real-time.
Data Source
AI summary
Embodiments of the present disclosure provide an image processing method, an electronic device, and a storage medium. The method includes: obtaining an image to be processed and a target color card, where the image to be processed includes a target layer set, and the target layer set includes a material layer, where the material layer includes target materials of the image to be processed; grouping the target materials based on material attributes of the target materials, to obtain at least one material group; and determining a mapping relationship between the at least one material group and candidate colors in the target color card, obtaining a target color corresponding to each material group of the at least one material group based on the mapping relationship, and updating colors of target materials in each material group based on the target color.