Currently, in our Augraphy repo we have a proper paper phase where we overlay textures on top of the images.
However, we have recognized the need to create more extensive and diverse set of textures to further enhance the quality and variability of synthetic data generated by Augraphy. To address this, we are thinking to generate additional textures by manipulating the existing set of diverse textures through addition, subtraction and multiplication of their features.
Extract Features from Each Texture for Texture Manipulation
Feature Extraction
Haralick Features: Haralick features are a good way to distinguish between different textures. These texture features quantify the feel, appearance, or consistency of a surface.
Additional features like color histograms can also be used to extract features and generate the synthetic dataset.
Blending
Addition and Subtraction: Combine the features of two textures by adding or subtracting corresponding feature values. Experiment with different weightings or scaling factors to control the intensity of the manipulation.
Feature Multiplication: Multiply selected features from one texture with features from another texture to generate unique combinations.
Texture Synthesis
The Efros-Leung Algorithm looks promising for generating new textures.
Problem Statement
Currently, in our Augraphy repo we have a proper paper phase where we overlay textures on top of the images. However, we have recognized the need to create more extensive and diverse set of textures to further enhance the quality and variability of synthetic data generated by Augraphy. To address this, we are thinking to generate additional textures by manipulating the existing set of diverse textures through addition, subtraction and multiplication of their features.
Extract Features from Each Texture for Texture Manipulation
Feature Extraction
Blending
Texture Synthesis
Links