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Title: Structural analysis and classification of patterns
Author: Plummer, A. P. N.
ISNI:       0000 0001 3492 9764
Awarding Body: Royal Holloway, University of London
Current Institution: Royal Holloway, University of London
Date of Award: 1980
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This work concerns the development of efficient methods for the recognition of binary picture objects, with a view to applications such as automatic location or inspection of industrial components and optical character recognition. Most common pattern recognition schemes attempt to overcome the high dimensionality of an input picture by taking feature measurements from it, which it is hoped will retain sufficient 'useful' information to enable correct classification to be made. If features are chosen on an 'ad hoc' basis as is often the case, there may be a loss of 'useful' information in the transformation from picture to feature space. Thus the error rate of the subsequent classifier may be increased. Furthermore, there is no easy way of estimating the increase in error rate. One way of ensuring zero loss of information in the transformation to feature space is to use a reversible transformation, which by suitable coding removes much of the redundancy in the original picture. A number of possible picture coding methods are examined. Of these, skeleton coding is chosen as being most suitable. The technique adopted thus involves the reduction of a binary picture object to a skeleton. By means of topological analysis and limb measurements, a feature vector is then produced suitable for subsequent classification by a nearest neighbour classifier. In order to be of practical use, any pattern recognition scheme must be capable of efficient implementation on readily available hardware. Thus much consideration has been given to the implementation of the algorithms described. In addition a study has been made of various types of hardware for picture processing. During the course of the work, a number of useful hardware and software tools were developed. These are described in some detail, and include an interactive system for the development of picture processing algorithms •
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Pattern recognition & image processing