ABSTRACT
Computer vision is a project to reproduce the remarkable performance of the human visual system (HVS) in a machine. It is both important and difficult. Some generic and particular applications are: medical diagnosis; quality inspection; robotics; driverless cars; missile guidance; car number plate recognition; pedestrian detection; and tracking people in a crowd. Image recognition and identification in complex scenes are the areas most actively researched. Computer vision is conventionally divided into three functional areas: low-level, mid-level, and high-level vision. This division follows a hierarchical approach to the HVS. Low-level vision covers the segmentation of the image taking place between the eye and the cortex. Mid-level vision, involving colour, form, and movement, occurs in the prestriate cortex. Finally, high-level vision, such as recognition, occurs in the inferior temporal cortex. The neural signals do not travel in a single direction from the low- to the high- level: there is a feedback of neural activity between the three divisions. Experimental data show that visual comprehension of images is fast [206]. This has been explained on the basis of modelling using feature 2extraction operating within a hierarchical feedforward neural network architecture [234].
