Bump Map Generation with Multi-Scale Texture Control
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Solution Overview
Problem
Existing techniques for generating bump and normal maps require manual effort, are time-consuming, and automated methods lack user control and accuracy, often resulting in undesired textures.
Innovation Solution
A system and method that allow users to generate bump and normal maps from images with user-specified weights, utilizing image derivatives of varying resolution and sharpness, and converting images to lab color space to separate luminance and color components, enabling precise control over texture appearance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated techniques are used to create bump and normal maps from texture images, then productivity is improved and time consumption is reduced, but manufacturing precision deteriorates and the accuracy of texture representation is insufficient
Solution Approach 1:
The patent segments the texture analysis into multiple frequency bands using Gaussian pyramid decomposition. The texture image is divided into coarse-scale and fine-scale components, allowing automated processing of different frequency ranges with appropriate algorithms for each, thereby maintaining both speed and accuracy
Solution Approach 2:
The patent transforms the problem into the frequency domain by applying Fourier transform and analyzing different frequency components. By changing the parameter space from spatial domain to frequency domain, the system can automatically extract texture features at multiple scales, improving both automation accuracy and user control
2Manufacturing precision
If manual techniques are used to define bump and normal maps, then manufacturing precision is improved and desired appearance is achieved, but productivity deteriorates and time consumption increases
Solution Approach 1:
The system performs self-service by automatically analyzing the input texture image and generating bump and normal maps without requiring manual pixel-by-pixel editing. The automated algorithm extracts texture features, computes surface normals, and generates the final maps, freeing users from tedious manual work while maintaining reasonable accuracy
Solution Approach 2:
The patent introduces an intermediary processing stage that converts the original texture image into frequency-domain representation and extracts texture features automatically. This intermediary step acts as a bridge between the input image and the final bump/normal maps, enabling automated generation with improved accuracy
3Ease of operation
If automated techniques create bump and normal maps without user control, then ease of operation is improved and special skills are not required, but manufacturing precision deteriorates and user satisfaction decreases
Solution Approach 1:
The patent implements dynamic control by allowing users to adjust parameters such as frequency band weights, bump map amplitude, and normal map scaling factors. These dynamic parameters enable users to fine-tune the automated generation process to achieve their desired appearance while maintaining ease of operation
Solution Approach 2:
The system incorporates feedback mechanisms where users can preview the generated bump and normal maps and adjust parameters iteratively. This feedback loop allows users to guide the automated process toward their aesthetic preferences, combining ease of automated operation with precision control over the final appearance
Data Source
AI summary
This disclosure relates to generating a bump map and/or a normal map from an image. For example, a method for generating a bump map includes receiving a texture image and a plurality of user-specified weights. The method further includes deriving a plurality of images from the texture image, the plurality of images vary from one another with respect to resolution or sharpness. The method further includes weighting individual images of the plurality of images according to the user-specified weights. The method further includes generating a bump map using the weighted individual images. The method further includes providing an image for display with texture added to a surface of an object in the image based on the bump map.