A software library by Alex Zvoleff enables calculation of image textures based on Grey-Level Co-Occurrence Matrices (GLCMs). The method implements the Haralick (1973) texture features and supports processing images that cannot fit in memory. The dataset nature is inferred from the platform and description, likely containing or generating texture feature data for images.
Use Cases
- Classifying materials in satellite or aerial imagery based on calculated texture features.
- Segmenting regions in medical scans using texture patterns derived from GLCMs.
- Training machine learning models for object recognition where texture is a discriminative feature.
- Analyzing artistic styles or forgeries in digital images based on texture statistics.
Strengths
- Implements the established Haralick (1973) method for texture analysis.
- Supports out-of-core processing for images larger than available memory.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- Last update date is unknown; freshness unverified.
Provenance
- Source
- Alex Zvoleff
- Collection Method
- Software library for calculating features from images.