Image segmentation refers to a process of dividing the image into disjoint regions that were meaningful. This process is fundamental in computer vision in that many applications, such as image retrieval, visual summary, image based modeling, and so on, can essentially benefit from it. This process is also challenging because the segmentation is usually subjective and the computation is highly costly. This book develops in turn the prior model for the pairwise graph approaches which is defined from multiple cues, a hyper graph based method which models multiple wise relations among the data points, and a tree structured graph based method which leads to an efficient and effective solution to the normalized cuts criterion. These approaches are demonstrated in multiple view, interactive and automatic image segmentation problems. This book is suitable for students and researchers in image processing, computer vision, pattern recognition and machine learning.
Image segmentation refers to a process of dividing the image into disjoint regions that were meaningful. This process is fundamental in computer vision in that many applications, such as image retrieval, visual summary, image based modeling, and so on, can essentially benefit from it. This process is also challenging because the segmentation is usually subjective and the computation is highly costly. This book develops in turn the prior model for the pairwise graph approaches which is defined from multiple cues, a hyper graph based method which models multiple wise relations among the data points, and a tree structured graph based method which leads to an efficient and effective solution to the normalized cuts criterion. These approaches are demonstrated in multiple view, interactive and automatic image segmentation problems. This book is suitable for students and researchers in image processing, computer vision, pattern recognition and machine learning.
Medical imaging is an important topic and plays a key role in robust diagnosis and patient care. It has experienced an explosive growth over the last few years due to imaging modalities such as...
Image Segmentation Summarizes and improves new theory, methods, and applications of current image segmentation approaches, written by leaders in the field The process of image segmentation divides...
Semantic image segmentation (SiS) plays a fundamental role towards a general understanding of the image content and context, in a broad variety of computer vision applications, thus providing key...
As one of the most important tasks in biomedical imaging, image segmentation provides the foundation for quantitative reasoning and diagnostic techniques. A large variety of different imaging...
Image Segmentation is an image processing technique which is used to subdivide an image into regions in which each one contains components having similar properties or characteristics. Its goal is...
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