Object-oriented language for image and vision execution

Abstract

Hardware technology advances have dramatically reduced the cost of image computation for machine vision; unfortunately, machine vision software technology has not kept pace. This paper presents OLIVE, an object-oriented language for machine vision and image processing, intended to make it easier to develop efficient, portable applications. First, OLIVE's principal object types are defined - IMAGEs and LOCUSes (abstractions of point sets and geometric entities) - and their corresponding operations, including the use of LOCUSes as generalized indexes for IMAGEs. Next, a hardware architecture that simplifies the implementation while enhancing performance is discussed. Finally, the authors compare the IMAGE/LOCUS objects to the IMAGE/TEMPLATE objects of the image algebra proposed by Ritter,Wilson and Davidson.