Multisensor Fusion for Automatic Scene Interpretation

Abstract

The area of computer analysis of images for automated detection and classification of objects in a scene has been intensively researched in the recent past. Two kinds of approaches may be noted in current and past research in machine perception - (1) To model the functions of biological vision systems, e.g., edge detection by the human visual system, and (2) To develop a scheme which a machine can use for accomplishing a particular task, e.g. automated detection of faulty placement of components on a printed circuit board. The latter approach produces a scheme that is application specific. In developing a scheme for a particular machine perception task one has a wide choice of sensing modalities and techniques to interpret the sensed signals. One is not limited by characteristics of a biological vision system that one is forced to emulate in the first approach, not even by the restriction that system emulate only the observed behavior of the biological system.