Texture Feature

Texture features, representing the spatial arrangement of image intensities, are crucial for various computer vision tasks, aiming to improve object recognition, image analysis, and anomaly detection. Current research focuses on developing robust texture descriptors using techniques like convolutional neural networks (CNNs), transformers, and novel algorithms that leverage shape information alongside texture, addressing limitations of texture-biased CNNs. These advancements have significant implications across diverse fields, including medical image analysis, robotics (e.g., object grasping), and security (e.g., deepfake detection), by enhancing the accuracy and efficiency of image processing and classification systems.