Image Co-segmentation / by Avik Hati, Rajbabu Velmurugan, Sayan Banerjee, Subhasis Chaudhuri.

Format:

Book

Author/Creator:

Hati, Avik, author.

Series:

Studies in Computational Intelligence, 1860-9503 ; 1082

Language:

English

Subjects (All):

Signal processing.

Image processing.

Signal, Speech and Image Processing.

Digital and Analog Signal Processing.

Image Processing.

Local Subjects:

Signal, Speech and Image Processing.

Digital and Analog Signal Processing.

Image Processing.

Physical Description:

1 online resource (231 pages)

Edition:

1st ed. 2023.

Place of Publication:

Singapore : Springer Nature Singapore : Imprint: Springer, 2023.

Summary:

This book presents and analyzes methods to perform image co-segmentation. In this book, the authors describe efficient solutions to this problem ensuring robustness and accuracy, and provide theoretical analysis for the same. Six different methods for image co-segmentation are presented. These methods use concepts from statistical mode detection, subgraph matching, latent class graph, region growing, graph CNN, conditional encoder–decoder network, meta-learning, conditional variational encoder–decoder, and attention mechanisms. The authors have included several block diagrams and illustrative examples for the ease of readers. This book is a highly useful resource to researchers and academicians not only in the specific area of image co-segmentation but also in related areas of image processing, graph neural networks, statistical learning, and few-shot learning.

Contents:

Introduction

Survey of Image Co-segmentation

Mathematical Background

Co-segmentation using a Classification Framework

Use of Maximum Common Subgraph Matching

Maximally Occurring Common Subgraph Matching

Co-segmentation using Graph Convolutional Neural Network

Use of a Conditional Siamese Convolutional Network

Few-shot Learning for Co-segmentation

Conclusions.

Other Format:

Print version: Hati, Avik Image Co-Segmentation

ISBN:

981-19-8570-7