Binarized HOG

Binarized HOG (Histogram of Oriented Gradients) is a technique in image processing that simplifies how we analyze shapes and textures. It involves capturing the direction of edges or lines in an image, then converting these details into a simplified, binary format—using just two states (like black and white). This approach reduces complexity, making it easier for computers to quickly recognize patterns like objects or features within an image. Essentially, it transforms detailed gradient information into a straightforward, efficient representation for tasks such as object detection and image recognition.