Thesis (Ph. D.)--Virginia Polytechnic Institute and State University, 1991. / Vita. Abstract. Includes bibliographical references (leaves 184-191). Also available via the Internet.

Most current machine vision systems for industrial inspection were developed with one specific task in mind. Due to the requirement for real-time operation, these systems are typically implemented in special purpose hardware that performs very specific operations. Hence, these systems inflexible in the sense that they cannot easily be adapted to other applications. However, current trends in computer technology suggests that low-cost general-purpose computers will be available in the very near future that are fast enough to meet the speed requirements of many industrial inspection problems. If this low-cost computing power is to be effectively utilized on industrial inspection problems, more general-purpose vision systems must be developed, vision systems that can be easily adapted to a variety of applications. Unfortunately, little research has gone into creating such general-purpose industrial inspection systems. In this dissertation, a general vision system framework has been developed that can be easily adapted to a variety of industrial web inspection problems. The objective of this system is to automatically locate and identify "defects" on the surface of the material being inspected. This framework is designed to be robust, to be flexible, and to be as computationally simple as possible. To assure robustness this framework employs a combined strategy of top-down and bottom-up control, hierarchical defect models, and uncertain reasoning methods. To make this framework flexible, a modular Blackboard framework is employed. To minimize computational complexity the system incorporates a simple multi-thresholding segmentation scheme, a fuzzy logic focus of attention mechanism for scene analysis operations, and a partitioning of knowledge that allows concurrent parallel processing during recognition. Based on the proposed vision system framework, a computer vision system for automated lumber grading has been developed. The purpose of this vision system is to locate and identify grading defects on rough hardwood lumber in a species independent manner. This problem seems to represent one of the more difficult and complex web inspection problems. The system has been tested on approximately 100 boards from several different species. Three different methods for performing label verification were tested and compared. These are a rule-based approach, a k-nearest neighbor approach, and a neural network approach. The results of these tests together with other considerations suggest that the neural network approach is the better choice and hence is the one selected for use in the vision system framework. Also, a new back-propagation learning algorithm using a steep activation function was developed that is much faster and more stable than the standard back-propagation learning algorithm. This algorithm was designed to speed the learning process involved in training a neural network to do label verification. However this algorithm seems to have general applicability. / Ph. D.

Thesis (MScEng (Mechanical and Mechatronic Engineering))--University of Stellenbosch, 2011. / ENGLISH ABSTRACT: The In the Physiotherapy Division of the Faculty of Health Sciences on the Tygerberg Hospital Campus of the University of Stellenbosch, the challenge arose to develop a portable, affordable and yet accurate 3D measurement machine for the assessment of posture in school children in their classroom environment. Currently Division already uses a state-of-the-art VICON commercial medical measuring machine to measure human posture in 3D in their physiotherapy clinic, but the system is not portable and is too expensive to cart around to different places for testing. To respond to this challenge, this Master’s thesis designed and analyzed a machine and its supporting system through both research on stereo-vision methodologies and empirical appraisal in the field. In the development process, the research was required to overcome the limitations posed by small image resolutions and lens distortions that are typical of cheap cameras. The academic challenge lay in the development of an error prediction model through Jacobian derivation and Error Propagation Law, to predict uncertainties of angular measurement calculated by the system. The research culminated in a system that is comparable in accuracy to the VICON within 3mm, and that has 1.5mm absolute accuracy within its own system for a measurement volume radius of 2.5 m. As such, the developed error model is an exact predictor of the angular error to within 0.02° of arc. These results, for both system accuracy and the error model, exceed the expectations on the basis of the initial challenge of the system. The development of the machine was successful in providing a prototype tool that is suitable for commercial development for use by physiotherapists in human posture measurement and assessment. In its current incarnation, the machine will also serve the Engineering Faculty as the most fundamental form of a three-dimensional measuring apparatus using only basic theories and algorithms of stereo-vision, thereby providing a basic experimental platform from which further scientific research on the theory and application of computer vision can be conducted. / AFRIKAANSE OPSOMMING: Die Fisioterapie Afdeling van die Fakulteit Gesondheidswetenskappe op die Tygerberg kampus van die Universiteit van Stellenbosch gebruik ’n allernuutste VICON kommersiële mediese meettoestel om menslike postuur in drie dimensies te meet. Vanuit hierdie Afdeling het die uitdaging ontstaan om ’n draagbare, bekostigbare, maar tog akkurate, drie-dimensionele meetapparaat geskik vir die meet van die postuur van skoolkinders in die klaskamer te ontwikkel. In aanvaarding van hierdie uitdaging, het hierdie Magistertesis ’n toestel en ondersteuningstels ontwerp en ontleed deur beide navorsing in stereo-visie metodiek en terplaatse beoordeling. In die ontwikkelingsproses moes die navorsing die beperkings wat deur klein-beeld resolusie en lens-distorsie (tipies van goedkoop kameras) meegebring word, oorkom. Die akademiese uitdaging lê in die ontwikkeling van ’n voorspellende foutmodel deur van die Jacobianse-afleiding en die Fout Propageringswet gebruik te maak om onsekerheid van hoeksberekening deur die stelsel te voorspel. Die navorsing het gelei tot ’n stelsel wat binne 3mm vergelykbaar is in akkuraatheid met dié van die VICON en ook 1.5mm absolute interne akkuraatheid het in ’n meet-volume radius van 2.5m radius. Die ontwikkelde foutmodel is dus ’n presiese voorspeller van hoekfout tot binne 0.02° van boog. Die resultate met betrekking tot beide die akkuraatheid en die foutmodel het die oorspronklike verwagtinge van die uitdaging oortref. Die ontwikkeling was suksesvol in die skep van ’n prototipe-toestel geskik vir kommersiële ontwikkeling, vir gebruik deur fisioterapeute in die meting en evaluering van menslike postuur. Die stelsel is in sy fundamentele vorm, deur die gebruik van slegs basiese teorieë en algoritmes van stereo-visie, funksioneer as ’n drie-dimensionele meetapparaat. In die fundamentele vorm sal die stelsel die Ingenieursfakulteit dien as ’n basiese eksperimentele platform waarop verdere wetenskaplike navorsing in die teorie en toepassing van rekenaar-visie gedoen kan word.