'advances In Image Segmentation' Ed. By Pei-gee Peter
by Pei-Gee Peter /
2013 / English / PDF
17.3 MB Download
This edition 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.
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.
Contents
Preface
1 Template Matching Approaches Applied to Vertebra Detection
2 Image Segmentation and Time Series Clustering Based on Spatial and Temporal ARMA Processes
3 Image Segmentation Through an Iterative Algorithm of the Mean Shift
4 Constrained Compound MRF Model with Bi-Level Line Field for Color Image Segmentation
5 Cognitive and Statistical Pattern Recognition Applied in Color and Texture Segmentation for Natu
with TOC BookMarkLinks
