Local Binary Pattern

Local Binary Patterns (LBPs) are a powerful image processing technique used to describe local texture features by thresholding pixel neighborhood intensities. Current research focuses on enhancing LBP's robustness and efficiency, including optimizing its mathematical representation, integrating it with deep learning models (like CNNs), and adapting it for various applications such as anomaly detection and biometric authentication. These advancements improve the accuracy and speed of image analysis tasks across diverse fields, from medical image analysis (e.g., detecting kidney abnormalities) to security applications (e.g., face anti-spoofing). The ongoing development of LBP-based methods contributes significantly to improving the performance and efficiency of computer vision systems.