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Computer Vision Techniques lor Industrial Applications and Robot Control

IP.com Disclosure Number: IPCOM000131561D
Original Publication Date: 1982-Dec-01
Included in the Prior Art Database: 2005-Nov-11
Document File: 26 page(s) / 79K

Publishing Venue

Software Patent Institute

Related People

Rafael C. Gonzalez: AUTHOR [+4]

Abstract

Because robots that ";see"; and ";feel"; can perform more complex tasks, industry has employed various computer vision techniques to enhance the abilities of intelligent machines.

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THIS DOCUMENT IS AN APPROXIMATE REPRESENTATION OF THE ORIGINAL.

This record contains textual material that is copyright ©; 1982 by the Institute of Electrical and Electronics Engineers, Inc. All rights reserved. Contact the IEEE Computer Society http://www.computer.org/ (714-821-8380) for copies of the complete work that was the source of this textual material and for all use beyond that as a record from the SPI Database.

Computer Vision Techniques lor Industrial Applications and Robot Control

Rafael C. Gonzalez and Reza Safabakhsh

University of Tennessee

Because robots that "see" and "feel" can perform more complex tasks, industry has employed various computer vision techniques to enhance the abilities of intelligent machines.

The recent widespread interest in robotics and automation in the US originates from American industry's most fundamental problem: a staggering drop in productivity. >From 1947 to 1965, US productivity increased at an average rate of 3.4 percent a year. The growth rate decreased to 2.3 percent in the following decade, then dropped to below one percent in the late 1970's and down to -0.9 percent in 1980. Japan's productivity growth, the contrasting example most often cited in the literature, has been climbing at an average annual rate of about 7.3 percent. I

Although there are many ways to influence manufacturing productivity and product quality -- regulatory, fiscal, and social -- the emphasis in the following discussion is technological. In particular, we are interested in the computer vision aspects of industrial inspection and robot control.

The principal motivation behind computer vision is increased flexibility and lower cost. The use of sensing technology to endow a machine with a greater degree of "intelligence" in dealing with its environment is receiving increased attention. A robot that can "see" and "feel" should be easier to train in the performance of complex tasks while at the same time requiring less stringent control mechanisms than preprogrammed machines. A sensory, trainable system is also adaptable to a much larger variety of tasks, thus achieving a degree of universality that ultimately translates into lower production and maintenance costs.

The computer vision process can be divided into five principal areas: sensing, segmentation, description, recognition, and interpretation. These categories are suggested to a large extent by the way computer vision systems are generally implemented. It is not implied that

human vision and reasoning can be so neatly subdivided nor that these processes are carried out independently of each other. For instance, we can logically assume that recognition and interpretation are highly interrelated functions in a human. These relationships, however are not yet understood to the point where they can be modeled analytically. Thus, the subdivision of functions discussed below can be viewed as a practical (albeit limited) approach for implementing state-of-the-a...