TY - CHAP A1 - Qiang He A2 - Chee-Hung Henry Chu ED1 - Pei-Gee Ho Y1 - 2011-04-19 PY - 2011 T1 - Image Segmentation Using Maximum Spanning Tree on Affinity Matrix N2 - It was estimated that 80% of the information received by human is visual. Image processing is evolving fast and continually. During the past 10 years, there has been a significant research increase in image segmentation. To study a specific object in an image, its boundary can be highlighted by an image segmentation procedure. The objective of the image segmentation is to simplify the representation of pictures into meaningful information by partitioning into image regions. Image segmentation is a technique to locate certain objects or boundaries within an image. There are many algorithms and techniques have been developed to solve image segmentation problems, the research topics in this book such as level set, active contour, AR time series image modeling, Support Vector Machines, Pixon based image segmentations, region similarity metric based technique, statistical ANN and JSEG algorithm were written in details. This book brings together many different aspects of the current research on several fields associated to digital image segmentation. Four parts allowed gathering the 27 chapters around the following topics: Survey of Image Segmentation Algorithms, Image Segmentation methods, Image Segmentation Applications and Hardware Implementation. The readers will find the contents in this book enjoyable and get many helpful ideas and overviews on their own study. BT - Image Segmentation SP - Ch. 8 UR - https://doi.org/10.5772/15589 DO - 10.5772/15589 SN - PB - IntechOpen CY - Rijeka Y2 - 2020-08-04 ER -