Applied Graph Theory in Computer Vision and Pattern Recognition
By:Abraham Kandel,Horst Bunke,Mark Last
Published on 2007-03-12 by Springer Science & Business Media
This book will serve as a foundation for a variety of useful applications of graph theory to computer vision, pattern recognition, and related areas. It covers a representative set of novel graph-theoretic methods for complex computer vision and pattern recognition tasks. The first part of the book presents the application of graph theory to low-level processing of digital images such as a new method for partitioning a given image into a hierarchy of homogeneous areas using graph pyramids, or a study of the relationship between graph theory and digital topology. Part II presents graph-theoretic learning algorithms for high-level computer vision and pattern recognition applications, including a survey of graph based methodologies for pattern recognition and computer vision, a presentation of a series of computationally efficient algorithms for testing graph isomorphism and related graph matching tasks in pattern recognition and a new graph distance measure to be used for solving graph matching problems. Finally, Part III provides detailed descriptions of several applications of graph-based methods to real-world pattern recognition tasks. It includes a critical review of the main graph-based and structural methods for fingerprint classification, a new method to visualize time series of graphs, and potential applications in computer network monitoring and abnormal event detection.
This Book was ranked at 40 by Google Books for keyword computer.
Book ID of Applied Graph Theory in Computer Vision and Pattern Recognition's Books is t4qHZ-aqzg4C, Book which was written byAbraham Kandel,Horst Bunke,Mark Lasthave ETAG "JU8xbjdYftc"
Book which was published by Springer Science & Business Media since 2007-03-12 have ISBNs, ISBN 13 Code is 9783540680192 and ISBN 10 Code is 3540680195
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