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About this issue
Pattern Recognition Pergamon Press 1968. Vol. I, pp. I 2.
Printed in Great Britain
About this Issue •
THE JOURNAL OF THE SOCIETY
Pattern Recognition is the official journal of the Pattern Recognition Society. The Society was formed to fill a need for information exchange among research workers in the patternrecognition field. Up to now, we "pattern-recognitionophiles" have been tagging along in computer science, information theory, optical processing techniques, and other miscellaneous fields. Because this work in pattern recognition presently appears in widely spread articles and as isolated lectures in conferences in many diverse areas, the purpose of the Journal Pattern Recognition is to give all of us an opportunity to get together in one place to publish our work. The Journal will thereby expedite communication among research scientists interested in pattern recognition. We consider pattern recognition in the broad sense, and we assume that the Journal will be read by people with a common interest in pattern recognition but from many diverse backgrounds. These include high energy physics, target recognition, biological taxonomy, meteorology, space science, oceanography, character recognition, optical instrumentation, industrial applications, neuron physiology, and many others. •
POLICIES AND PROSPECTIVES
The publication policy is to publish (1) new original articles that have been appropriately reviewed by competent scientific people, (2) reviews of developments in the field, and (3) pedagogical papers covering specific areas of interest in pattern recognition. Special issues of Pattern Recognition are planned on Instrumentation, the Theory of Pattern Recognition, Character Recognition, Biomedical Pattern Recognition, Pattern Recognition in Psychophysics, Environmental Sciences, High Energy Physics, Industrial Applications, Neuron Physiology, Space Applications, Time-Dependent Pattern Recognition, Linear Discrimination, Snytax-Directed Pattern Recognition, and Computer Programs Developed for Pattern Recognition. •
IN THIS FIRST ISSUE
This inaugural issue, however, is concerned with general methodologies rather than with specific applications, and indicates the wide variety of methods that can be applied to pattern recognition. In the first article, we are concerned with feature extraction in pattern recognition. Here Prof. Tou envisions pattern recognition of concrete items, as distinguished from abstract it, ns, in terms of the three main steps of sensing or identifying input data, extracting characteristic features of this data, and finally making the identification of the object being recognized. He presents a general approach, dealing with pattern classes and feature vectors. On the other hand, Dr. Beisner presents a different, recursive Bayesian approach to pattern recognition. Again, a vector is used to characterize the input pattern data and a proper classification is sought as the solution to the problem of recognizing the pattern.
2
About this issue
Conditional probabilities are utilized and the objective is to find a training algorithm by means of which certain initially unspecified parameters can be determined to make the proper classification. The training program determines the value of the parameters, which together with the input pattern, can be used to determine the probability with which it can be said that the input pattern belongs to a particular classification. From such abstract patterns which are represented by vectors characteristics, we turn our attention in the next paper to actual pictures. Prof. Azriel Rosenfeld and Mr. John L. Pfaltz describe a technique of picture analysis which utilizes distance functions. These techniques are required when it is necessary to relate the boundary of an object to its interior, or more generally, to relate one aspect of a pictorial feature with other aspects at a distance. The problem here is more computer oriented and is concerned mainly with algorithms for computing such distance functions. The paper is generously illustrated with actual computer printouts. Many, if not most, of the pattern recognition problems that occur in practical application will utilize computer methods in some form. The use of the computer requires exacting and precise notation for the representation of concepts in pattern recognition, and Dr. R. B. Banerji proposes one such language. An analysis of the problems involved in setting up such a language is given and particular "machineries of the language" are described. Some manipulations in the language are then illustrated. Pattern recognition lies by no means solely in the realm of the mathematician or engineer. This is certainly illustrated by Dr. Rosalie Dunn and Prof. R. A. Davidson in their article on pattern recognition in biological classification. In fact, as these authors point out, pattern recognition is possibly even more important in studying the biological environment than in consideration of many aspects of the physical sciences. However, the inherent complexity that so commonly occurs in biological problems still shows in their treatment and illustrations. •
FOR THE NON-MATHEMATICIAN ALSO
In summary, I feel that this first issue of Pattern Recognition illustrates the many points of view that can be brought to bear on the basic methodological aspects of this subject. However, as editor, I would like to apologize a little for the fact that almost all the papers include highly mathematical treatments. This mathematical sophistication is of course required when basic methodologies are being discussed, but in practice and application of pattern recognition to particular real world problems, such mathematical abstraction must give way to realizable algorithms which can be explained in terms of the subject matter of the specific application. I therefore hope that those of us who are not extremely mathematically inclined will bear with our methodologists for this issue and will believe me when I say that pattern recognition is not a field coveted by mathematicians.
ROBERT S. LEDLEY Editor-in-Chief
Printed in Great Britain
About this Issue •
THE JOURNAL OF THE SOCIETY
Pattern Recognition is the official journal of the Pattern Recognition Society. The Society was formed to fill a need for information exchange among research workers in the patternrecognition field. Up to now, we "pattern-recognitionophiles" have been tagging along in computer science, information theory, optical processing techniques, and other miscellaneous fields. Because this work in pattern recognition presently appears in widely spread articles and as isolated lectures in conferences in many diverse areas, the purpose of the Journal Pattern Recognition is to give all of us an opportunity to get together in one place to publish our work. The Journal will thereby expedite communication among research scientists interested in pattern recognition. We consider pattern recognition in the broad sense, and we assume that the Journal will be read by people with a common interest in pattern recognition but from many diverse backgrounds. These include high energy physics, target recognition, biological taxonomy, meteorology, space science, oceanography, character recognition, optical instrumentation, industrial applications, neuron physiology, and many others. •
POLICIES AND PROSPECTIVES
The publication policy is to publish (1) new original articles that have been appropriately reviewed by competent scientific people, (2) reviews of developments in the field, and (3) pedagogical papers covering specific areas of interest in pattern recognition. Special issues of Pattern Recognition are planned on Instrumentation, the Theory of Pattern Recognition, Character Recognition, Biomedical Pattern Recognition, Pattern Recognition in Psychophysics, Environmental Sciences, High Energy Physics, Industrial Applications, Neuron Physiology, Space Applications, Time-Dependent Pattern Recognition, Linear Discrimination, Snytax-Directed Pattern Recognition, and Computer Programs Developed for Pattern Recognition. •
IN THIS FIRST ISSUE
This inaugural issue, however, is concerned with general methodologies rather than with specific applications, and indicates the wide variety of methods that can be applied to pattern recognition. In the first article, we are concerned with feature extraction in pattern recognition. Here Prof. Tou envisions pattern recognition of concrete items, as distinguished from abstract it, ns, in terms of the three main steps of sensing or identifying input data, extracting characteristic features of this data, and finally making the identification of the object being recognized. He presents a general approach, dealing with pattern classes and feature vectors. On the other hand, Dr. Beisner presents a different, recursive Bayesian approach to pattern recognition. Again, a vector is used to characterize the input pattern data and a proper classification is sought as the solution to the problem of recognizing the pattern.
2
About this issue
Conditional probabilities are utilized and the objective is to find a training algorithm by means of which certain initially unspecified parameters can be determined to make the proper classification. The training program determines the value of the parameters, which together with the input pattern, can be used to determine the probability with which it can be said that the input pattern belongs to a particular classification. From such abstract patterns which are represented by vectors characteristics, we turn our attention in the next paper to actual pictures. Prof. Azriel Rosenfeld and Mr. John L. Pfaltz describe a technique of picture analysis which utilizes distance functions. These techniques are required when it is necessary to relate the boundary of an object to its interior, or more generally, to relate one aspect of a pictorial feature with other aspects at a distance. The problem here is more computer oriented and is concerned mainly with algorithms for computing such distance functions. The paper is generously illustrated with actual computer printouts. Many, if not most, of the pattern recognition problems that occur in practical application will utilize computer methods in some form. The use of the computer requires exacting and precise notation for the representation of concepts in pattern recognition, and Dr. R. B. Banerji proposes one such language. An analysis of the problems involved in setting up such a language is given and particular "machineries of the language" are described. Some manipulations in the language are then illustrated. Pattern recognition lies by no means solely in the realm of the mathematician or engineer. This is certainly illustrated by Dr. Rosalie Dunn and Prof. R. A. Davidson in their article on pattern recognition in biological classification. In fact, as these authors point out, pattern recognition is possibly even more important in studying the biological environment than in consideration of many aspects of the physical sciences. However, the inherent complexity that so commonly occurs in biological problems still shows in their treatment and illustrations. •
FOR THE NON-MATHEMATICIAN ALSO
In summary, I feel that this first issue of Pattern Recognition illustrates the many points of view that can be brought to bear on the basic methodological aspects of this subject. However, as editor, I would like to apologize a little for the fact that almost all the papers include highly mathematical treatments. This mathematical sophistication is of course required when basic methodologies are being discussed, but in practice and application of pattern recognition to particular real world problems, such mathematical abstraction must give way to realizable algorithms which can be explained in terms of the subject matter of the specific application. I therefore hope that those of us who are not extremely mathematically inclined will bear with our methodologists for this issue and will believe me when I say that pattern recognition is not a field coveted by mathematicians.
ROBERT S. LEDLEY Editor-in-Chief