Feature Extraction

Feature extraction is the process of identifying and isolating measurable properties or characteristics (features) from raw data such as images, audio, or text, for use in machine learning tasks. In image processing, features may include edges, textures, colours, shapes, or higher-level semantic properties captured by neural network layers. For accessibility, feature extraction underpins technologies such as automatic image description, object recognition in screen readers, and AI-assisted cataloguing of visual cultural heritage collections. The quality and diversity of extracted features directly affects how well AI systems can describe content to users who cannot access the visual information directly — making feature extraction a foundational concern for accessible AI.