Advanced Image and Video Processing Using MATLAB利用

文件名称: Advanced Image and Video Processing Using MATLAB

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详细说明：利用MATLAB进行高级图像和视频处理，分享给大家学习使用。The book series Modeling and Optimization in Science and Technologies(Most) publishes basic principles as well as novel theories and methods in the fast-evolving field of modeling and optimization Topics of interest include, but are not limited to methods for analysis, design and control of complex systems, networks and machines; methods for analysis, visualization and management of large data sets use of supercomputers for modeling complex systems; digital signal processing molecular modeling; and tools and software solutions for different scientific and technological purposes. Special emphasis is given to publications discussing novel theories and practical solutions that, by overcoming the limitations of traditional methods, may successfully address modern scientific challenges, thus promoting scientific and technological progress. The series publishes monographs, contributed volumes and conference proceedings, as well as advanced textbooks. The main targets of the series are graduate students, researchers and professionals working at the forefront of their field Moreinformationaboutthisseriesathttp://www.springer.com/series/10577 Shengrong Gong. Chunping liu YiJi. Baojiang Zhong. Yonggang Li Husheng Dong Advanced Image and video Processing Using MatLaB S ringer Shengrong on Baojiang Zhong School of Computer Science School of Computer science and Engineering and Technology Changshu Institute of Technology Soochow University Changshu. Jiangsu China Suzhou, Jiangsu. China Chunping liu Yonggang Li School of computer Science College of mathematics physics and Technology and Information Engineering Soochow university Jiaxing Universit Suzhou, jiangsu. China Jiaxing, Zhejiang, China YiJi Husheng Dong School of Computer Science School of Computer Science and Technology and Technology Soochow universit Soochow University Suzhou, Jiangsu, China Suzhou. jiangsu. china ISSN2196-7326 issn 2196-7334(electronic) Modeling and Optimization in Science and Technologies ISBN978-3-319-772219 ISBN978-3-319-77223-3( e Book) https://doi.org/10.1007/978-3-319-77223-3 Library of Congress Control Number: 2018948687 C Springer International Publishing AG, part of Springer Nature 2019 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or diss similar methodology now known or hereafter developed The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use The publisher. the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to urisdictional claims in published maps and institutional affiliations This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Preface Digital image processing mainly focuses on the research of signal processing, such as image contrast adjustment, image coding, image denoising and filtering. It is different that Image analysis emphasizes describing images with symbolic repre sentations, analysis, interpretation, and recognition. along with the boom in arti ficial intelligent and deep learning, digital image processing is going deeper and more advanced. People start the researches in simulating the human vision to see, to understand, and even to explain the real world using three techniques: image segmentation, image analysis, and image understanding. The Image segmentation is to extract the features such as the edges and regions for image analyzing, recog- nition,and understanding. Image analysis is to extract intelligent information from underlying features and their relationship using mathematical models and Image processing techniques. Image analysis and image processing are closely related Although there may be a certain degree of overlapping, they are different in essence. Therefore, image analysis is more related to pattern recognition and computer vision. It is generally used to analyze the underlying features and superstructures by some mathematical models The researches of image analysis are mainly focused on content-based image retrieval, face recognition, emotion recognition, optical character recognition, handwriting recognition, biomedical image analysis, video object extraction. The Image understanding is to further understand the meanings and scenario explanations by researching the properties and relations of the features and objects. The objects for image understanding are symbols from description; the process is similar to human brain Corresponding to image analysis, video analysis is to analyze the video frames of surveillance camera using computer vision techniques. It is also able to filter the background such as wind, rain, snow, fallen leaves, birds, and floating flags It is so called object tracking in complex background. Due to the variant illusion, motion, occlusion, color, and complex background, the difficulty of object detection and tracking algorithm design is increased eface The steps in image and video analysis mainly include segmentation, classifica- tion, and explanation. The classification process normally extracts the features by SIFT and LBP. with the use of deep learning techniques, people start using deep feature by extracting automatically for image classification, scenario classification and behaviors analysis Our purpose in writing this book is to present advanced applications in image and video processing. We believed that this book is distinguished from other MATLAB-based fundamental textbooks which only introduces the basic functions such as the transform enhancement, restoration, coding and resizing of image Our book emphasized the advanced applications such as image dehazing correction image draining correction, image stitching, image watermarking, visual object recognition, moving object tracking, dynamic scene classification, pedestrian re-identification, behavior analysis with deep learning, and so on The book is divided into three parts Part I: The Basic Concepts Chapter I briefly introduces the fundamental principles including the analysis techniques: scene segmentation, feature description, and object recognition. There are also some summaries about examples of advanced applications, such as image fusion, image inpainting, image stitching, image watermarking, object tracking, and pedestrian re-identification Chapter 2 introduces the functions of matlab toolboxes for image and video processing Chapter 3 presents the image and video segmentation methods of threshold, region-based, partial differential equation, clustering, graph theory, and cumulative difference-based motion region extraction Chapter 4 presents the feature extraction and representations, which includes Harris corner detection, SUSAN edge detection, the point feature detection algo- rithm sift and sure Part II: Advances in Image Processing This part includes the image processing techniques such as image correction, image painting, image fusions, image stitching, image watermarking Chapter 5 firstly introduces three filters for image denoise and blurred functions Then, it mainly introduces the correction techniques of image dehazing, image draining, and text image feature correction rerace Chapter 6 presents the image inpainting techniques including the principle, structure, algorithm, and some example codes Chapter 7 firstly introduces the fusions types and their schemes and then men tioned a very important method: wavelet transform for image fusion. Finally, it discusses the evaluation of image fusion objectively and subjectively Chapter 8 introduces the image stitching techniques such as region-based feature-based, and feature point method. The SiFT and Harris corner detection algorithms are also introduced in this chapter Chapter 9 briefly introduces the image watermarking in three different trans forms which are spatial-domain-based, DCT-based and dWT-based watermarking techniques Chapter 10 introduces the object recognition techniques including face recog nition, facial expression, and image-to-character extraction and recognition Part II: Advances in Video Processing and then associated Chapters Chapters 11-14 mainly introduce the video processing techniques of moving object tracking dynamic scene classification based on tmBP, behavior recognition based on LDa topic model, person re-identification based on metric learning, lip recog- nition instance based on deep learning model, and deep cnn architecture for event recognition Chapter 1l introduces the object tracking techniques using Gaussian mixture model for background detection, and the ransac for feature points tracking Further extend the mean-shift object tracking algorithm Chapter 12 introduces the dynamic scene classification and discusses the TmBP and lda models for the classification Chapter 13 presents a person re-identification method by using the image understanding technique. Chapter 14 presents the deep learning in image and video understanding For the convenience of the readers to evaluate the performance of the algorithms we also give the common evaluation criteria in the appendix This book is written by Shengrong Gong, Chunping Liu, Yi Ji, Baojiang Zhong, Yonggang Li, Husheng Dong, Conghua Xie, Wei Pan, Yu xia, and Zhaohui Wang Our M.Sc. researchers take participate in debugging most of the programs. They are Xinhua Dai, Ran Yan, Zongming Bao, and Pengcheng Zhou We gratefully acknowledge the professional suggestions of the reviewers and editors of Springer Press. We also thank to the support of Changshu Institute of Technology and Soochow University. We appreciate the support of National Natural Science Foundation of China(NSFC Grant No. 61170124, 61272258 Preface 61301299), Integration of Cloud Computing and Big Data, Innovation of Science and Education(Grant No. 2017B03112), Provincial Natural Science Foundation of Jiangsu, China(Grant No. BK20151260, BK20151254), Six talent peaks project in Jiangsu Province, China(Grant No. DZXX-027) Changshu, China Shengrong gong Suzhou. China Chunping liu Suzhou. china Yi Ji Suzhou china Baojiang Zhong Jiaxing, China Yonggang Li Suzhou. China Husheng dong Contents Part I The Basic Concepts 1 Introduction 1.1 Basic Concepts and Terminology 1.1.1 Digital Image and digital video 1.1.2 Image processing 1.1.3 Image analysis 1. 1.4 Video analysis 1.2 Image and Video Analysis 333668990 1. 2. 1 Image and Video Scene segmentation 1.2.2 Image and video Feature Description 1.2.3 Object Recognition in Images/Videos 12 1.2.4 Scene Description and Understanding 13 1.3 Examples of Advanced Applications 14 1.3.1 Image Correction 14 1.3.2 Image Fusion 15 3.3 Digital Image Inpainting 15 1.3.4 Image stitching 16 1.3.5 Digital Watermarking 1.3.6 Visual Object Recognition 18 1.3.7 Object Tracking 20 1.3.8 Dynamic Scene Classification 1. 3.9 Pedestrian Re-identification 22 1.3.10 Lip Recognition in Video References 23 2 Matlab Functions of Image and video 27 2.1 Introduction to Matlab for Image and video 2.2 Basic elements of matlab 28

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