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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
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.
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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
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.