Image recognition is the ability of a machine or computer to see and identify places, logos, people, objects, buildings, and other variables in an image, where an image can be any graphic, still photo, and/or video. Image recognition not only identifies the content in the images, but performs a large number of machine-based visual tasks, such as labeling images with informational tags, searching the content in an image, such as identifying a cat in an image that has multiple animals in it and guiding autonomous robots and self-driving vehicles.

Human and animal brains recognize images and objects with ease, but it is extremely difficult for computers to perform the same task. Image recognition requires deep machine learning techniques. Image recognition tasks are best performed on convolution neural network-based processors. Image recognition algorithms perform tasks by use of comparative 3D models, comparing images taken from different angles using edge-detection techniques. These algorithms need to be trained with millions of already labeled pictures with guided computer learning.