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Pattern Recognition and Image Preprocessing (Electrical and Computer Engineering)

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This book is based in part on my earlier work. Pattern Recognition: Applications to Large Data-Set Problems, published by Marcel Dekker: Inc. in 1984. It was originally intended that this volume be a second editon of that work. However, due to the tremendous amount of material added it seemed that a new title. Pattern Recognition and Image Preprocessing, was more appropriate.

The materials collected for this book are grouped into four parts. Part One emphasizes the principles of decision theoretic pattern recognition. Part Two deals with data preprocessing for pictorial pattern recognition. Part Three gives some current examples of applications, and Part Four discusses some of the practical concerns in image preprocessing and pattern recognition.

Chapter 1 presents the fundamental concept of pattern recognition and its system configuration. Included are brief discussions of selected applications, including weather forecasting, handprinted character recognition, speech recognition, medical analysis, and satellite and aerial-photo interpretation. Also in Chapter 1, the two principal approaches used in pattern recognition, the decision theoretic and syntactic approaches, are described and compared.

The remaining chapters in Part One focus primarily on the decision theoretic approach. Because of space limitations, the syntactic approach is not covered. Chapters 2 and 3 discuss principles involved in nonparametric decision theoretic classification and the training of the discriminant functions used in these classifications. Chapter 4 introduces the principles of statistical pattern decision theory in classification. A great many advances have been made in recent years in the field of clustering. Because of the need to be systematic, the material in Chapter 5 was selected and organized to make readers aware of current trends and how to use these approaches in solving recognition problems.

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