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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Detalles Bibliográficos
Otros Autores: Peter Ho, Pei-Gee (Editor ), Ho, Pei-Gee, editor (editor)
Formato: Libro electrónico
Idioma:Inglés
Publicado: Rijeka, Croatia : IntechOpen 2012
[2012]
Materias:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009654696106719
Descripción
Sumario: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.
Descripción Física:1 online resource (128 pages) : illustrations
Bibliografía:Includes bibliographical references.
ISBN:9789535157199
Acceso:Open access