Attributes are extracted from images using computer vision techniques, often powered by machine learning or deep learning models. These attributes could include features like color, shape, texture, or specific object categories.
Deep learning models like CNNs automatically learn and extract attributes through feature maps generated at different layers. For example, in facial recognition, attributes such as age, gender, and emotion can be derived using pre-trained models.
Traditional methods like histogram analysis or edge detection can also be used to extract simpler attributes, depending on the complexity of the task and available resources.