Machine vision has been characterized by a lack of standards, which has resulted in the necessity for expensive customization of systems. Our objective is to investigate the development of a vision system which utilizes or establishes standards.To this end we chose to use laser triangulation, to incorporate television broadcast standards, and to implement the software in an object-oriented class library encapsulating the essential features of the major components of a vision system. A 3D color digitization system was conceived and implemented, based on existing standards, with the flexibility and extensibility provided by object-oriented software design. The system generated data in a standard 3D file format, and was used to digitize and create rendered images of a building.Although the construction of classes needed careful planning, once created they greatly facilitated system modification. Existing standards are suitable for use in a 3D vision system, but there are several limitations which are considered. INTRODUCTIONThere are numerous applications for 3D data acquisition systems, including supplying data for archival, analytical, and visualization purposes. Examples include robotics and CAD/CAM.It is easy to be impressed by the visual skills of animals such as ourselves. Unfortunately machine vision has some distance to travel before matching these abilities. A number of general problems have been emphasized in a recent review (1 -3), and it has been felt that a move towards standardization is desirable. Our data acquisition system has been designed to involve some major standards -namely broadcast television scanning and signal formats, a class library of object-oriented software, and a standard file format for the 3D data storage. These standard features allow for easy comprehension coupled with flexibility for future expansion and alteration. 3D data acquisition systems encompass a variety of different techniques that have been reviewed by Jarvis (4). They can be considered to fall into two major categories. The first tries to approach human vision. Human vision is clearly successful, but uses a very large database of information, generated from many years of experience in different situations. We use a variety of data inputs to give 3D perception, and these are fused together to form a useable model of reality. Machine vision systems that attempt to emulate human performance tend to be complex and ambiguous, but are potentially of wide application. Examples are the computer analysis of a 2D photograph of an outdoor scene so as to infer 3D from perceived occlusions in the scene, and less indirect techniques such as stereo disparity measurements involving matching identical points in stereo images (5). Downloaded From: http://proceedings.spiedigitallibrary.org/ on 06/25/2016 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspxThe second category of vision system is more direct in operation, and si:nce there is less classification or recognition of features, these systems retain detailed data with...

It is important to incorporate an introductory treatment of integrated circuits in the computer science curriculum in a liberal arts university. We use real world problems, such as the relationship between power consumption and circuit levels, to motivate students to learn.

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