Object recognition is a process for identifying a specific object in a digital image or video. Object recognition algorithms rely on matching, learning, or pattern recognition algorithms using appearance-based or feature-based techniques.
Object recognition is useful in applications such as video stabilization, advanced driver assistance systems (ADAS), and disease identification in bioimaging. Common techniques include deep learning based approaches such as convolutional neural networks, and feature-based approaches using edges, gradients, histogram of oriented gradients (HOG), Haar wavelets, and linear binary patterns.
You can recognize objects using a variety of models, including:
See also: Steve on Image Processing, image recognition, image processing and computer vision, object detection, face recogniton, MATLAB and OpenCV, feature extraction, stereo vision, optical flow, RANSAC, pattern recognition, point cloud, deep learning