Texture Image Collection for Computer Vision

Texture data from OpenML provides a resource for analyzing visual patterns and surface properties. The dataset's author, organization, and specific size are not documented. It is available through the OpenML platform.

Use Cases

• Classify material types based on texture patterns in image patches.
• Train generative adversarial networks (GANs) to synthesize new, realistic texture images.
• Benchmark feature extraction algorithms using texture descriptors like Local Binary Patterns (LBP).
• Develop models for texture segmentation within larger, more complex scenes.

Strengths

• Sourced from OpenML, a curated repository for machine learning datasets.
• Focuses on a specific, well-defined data domain (texture).

Limitations

• Unknown sample size prevents assessment of statistical power.
• Lack of column or feature descriptions limits understanding of data structure.
• No provenance details (author, collection method) affect reproducibility.

Provenance

Source

OpenML platform