Advances in Image Segmentation

The field of digital image segmentation is continually evolving. Most recently, the advanced segmentation methods such as Template Matching, Spatial and Temporal ARMA Processes, Mean Shift Iterative Algorithm, Constrained Compound Markov Random Field (CCMRF) model and Statistical Pattern Recognition...

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Bibliographic Details
Other Authors: Peter Ho, Pei-Gee (Editor), Ho, Pei-Gee, editor (editor)
Format: eBook
Language:Inglés
Published: Rijeka, Croatia : IntechOpen 2012
[2012]
Subjects:
See on Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009654696106719
Description
Summary:The field of digital image segmentation is continually evolving. Most recently, the advanced segmentation methods such as Template Matching, Spatial and Temporal ARMA Processes, Mean Shift Iterative Algorithm, Constrained Compound Markov Random Field (CCMRF) model and Statistical Pattern Recognition (SPR) methods form the core of a modernization effort that resulted in the current text. This new edition of "Advanced Image Segmentation" is but a reflection of the significant progress that has been made in the field of image segmentation in just the past few years. The book presented chapters that highlight frontier works in image information processing.
Physical Description:1 online resource (128 pages) : illustrations
Bibliography:Includes bibliographical references.
ISBN:9789535157199
Access:Open access