Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben

2019 | Buch

Introduction Kapitel lesen Erstes Kapitel lesen

Advanced Image and Video Processing Using MATLAB

verfasst von: Prof. Shengrong Gong, Prof. Chunping Liu, Dr. Yi Ji, Prof. Baojiang Zhong, Yonggang Li, Husheng Dong

Verlag: Springer International Publishing

Buchreihe : Modeling and Optimization in Science and Technologies

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

Einloggen, um Zugang zu erhalten
insite
SUCHEN

Über dieses Buch

This book offers a comprehensive introduction to advanced methods for image and video analysis and processing. It covers deraining, dehazing, inpainting, fusion, watermarking and stitching. It describes techniques for face and lip recognition, facial expression recognition, lip reading in videos, moving object tracking, dynamic scene classification, among others.

The book combines the latest machine learning methods with computer vision applications, covering topics such as event recognition based on deep learning，dynamic scene classification based on topic model, person re-identification based on metric learning and behavior analysis. It also offers a systematic introduction to image evaluation criteria showing how to use them in different experimental contexts.

The book offers an example-based practical guide to researchers, professionals and graduate students dealing with advanced problems in image analysis and computer vision.

Inhaltsverzeichnis

Frontmatter

The Basic Concepts

Frontmatter
Chapter 1. Introduction
Abstract
In this chapter we introduce some basic concepts and terminology about digital image and video analysis. Then some example applications are listed.
Shengrong Gong, Chunping Liu, Yi Ji, Baojiang Zhong, Yonggang Li, Husheng Dong
Chapter 2. Matlab Functions of Image and Video
Abstract
In this chapter, we begin introducing the basic usage of MATLAB. Then, some important tools for image and video processing are introduced, such as the graphics and visualization, the image processing toolbox, and the functions for processing video.
Shengrong Gong, Chunping Liu, Yi Ji, Baojiang Zhong, Yonggang Li, Husheng Dong
Chapter 3. Image and Video Segmentation
Abstract
This chapter is devoted to some segmentation method of image and video. For image segmentation, five types of methods are detailed, including threshold segmentation, region-based segmentation, partial differential equation based segmentation, clustering based segmentation, and the graph theory based segmentation. For video segmentation, we shall introduce the motion region extraction method based on cumulative difference.
Shengrong Gong, Chunping Liu, Yi Ji, Baojiang Zhong, Yonggang Li, Husheng Dong
Chapter 4. Feature Extraction and Representation
Abstract
This chapter is focused on some classical feature representations for image and video analysis. In particular, we will introduce the histogram-based features, texture features, and some local point features.
Shengrong Gong, Chunping Liu, Yi Ji, Baojiang Zhong, Yonggang Li, Husheng Dong

Advances in Image Processing

Frontmatter
Chapter 5. Image Correction
Abstract
In the process of image generation, transmission and recording, the quality of images will decrease due to various reasons, which will lead to the degradation of the image. Image correction refers to the restoration of distorted images. The causes of image distortion including: aberration, distortion and limited bandwidth of the imaging system; geometry distortion caused by photographic attitude and nonlinear sweep scanning of the imaging device; motion blur, radiation distortion and the noise-corruption. The basic idea of image correction is to establish the corresponding mathematical model based on the distortion reasons, extracting the needed information from the contaminated or distorted image signals, restore the image to its original appearance along the reverse process that distorts the image. The actual correction process is to design a filter to estimate pixel value of the original image from the distorted image which maximum close to the original images according to the prescribed error criterion.
Shengrong Gong, Chunping Liu, Yi Ji, Baojiang Zhong, Yonggang Li, Husheng Dong
Chapter 6. Image Inpainting
Abstract
In this chapter, the image inpainting algorithms are discussed. We first introduce the principle of image inpainting, and then two types of inpainting algorithms are detailed, including the vibrational PDE-based and exemplar-based inpainting.
Shengrong Gong, Chunping Liu, Yi Ji, Baojiang Zhong, Yonggang Li, Husheng Dong
Chapter 7. Image Fusion
Abstract
In this chapter we introduce the image fusion methods, including the wavelet transform based fusion, region based fusion and the fusion method based on fuzzy Dempster-Shafer evidence theory. Moreover, the image quality and fusion evaluations are also introduced. In this chapter we introduce the image fusion methods, including the wavelet transform based fusion, region based fusion and the fusion method based on fuzzy Dempster-Shafer evidence theory. Moreover, the image quality and fusion evaluations are also introduced.
Shengrong Gong, Chunping Liu, Yi Ji, Baojiang Zhong, Yonggang Li, Husheng Dong
Chapter 8. Image Stitching
Abstract
In this chapter we firstly introduce the application background and basic process of image stitching, then depict several image stitching methods based on region, image stitching methods based on feature points, and panoramic video image stitching techniques.
Shengrong Gong, Chunping Liu, Yi Ji, Baojiang Zhong, Yonggang Li, Husheng Dong
Chapter 9. Image Watermarking
Abstract
In this chapter we firstly introduce the application background of digital watermarking, then represent fragile watermarking, robust watermarking, and semi-fragile watermarking embedding methods respectively.
Shengrong Gong, Chunping Liu, Yi Ji, Baojiang Zhong, Yonggang Li, Husheng Dong
Chapter 10. Visual Object Recognition
Abstract
Object recognition, one of the important tasks of image recognition, mainly aimed at the recognition of visible images. It can accurately define and describe objects by attributes and features of geometric appearance, texture and material of images. In a broad sense, the recognition process can distinguish objects from backgrounds and other suspicious objects, such as cars and roads, that is the object detection.
Shengrong Gong, Chunping Liu, Yi Ji, Baojiang Zhong, Yonggang Li, Husheng Dong

Advances in Video Processing and then Associated Chapters

Frontmatter
Chapter 11. Visual Object Tracking
Abstract
Moving object tracking is to find out the candidate object region which is the most similar area in the image sequence through the effective expression of the object, that is to locate the target in the sequence image so as to obtain the complete motion trajectory of the moving target. In this chapter, we first introduce the moving object detection method in static background. We also present the Adaptive background modeling method by using a mixture Gaussians. In the next three sections, there are three methods for object tracking: Ransac, Meanshift and Particle Filter. In the last section, we introduce the multi-object tracking method.
Shengrong Gong, Chunping Liu, Yi Ji, Baojiang Zhong, Yonggang Li, Husheng Dong
Chapter 12. Dynamic Scene Classification Based on Topic Models
Abstract
This chapter briefly introduces the background reading of scene classification and two topic models: LDA model and Topic Model using Belief Propagation (TMBP).
Shengrong Gong, Chunping Liu, Yi Ji, Baojiang Zhong, Yonggang Li, Husheng Dong
Chapter 13. Image Understanding-Person Re-identification
Abstract
In this chapter, we talk about one of the typical image understanding problems—cross-camera person re-identification. Some classical visual descriptors and metric learning algorithms for person re-identification are detailed.
Shengrong Gong, Chunping Liu, Yi Ji, Baojiang Zhong, Yonggang Li, Husheng Dong
Chapter 14. Image and Video Understanding Based on Deep Learning
Abstract
In this chapter we firstly introduce the development and the main reasons of the success of deep learning, then the structure and principle of the deep CNN are explored, and several classical convolution network models are analyzed, finally two instances based on CNN architecture are given.
Shengrong Gong, Chunping Liu, Yi Ji, Baojiang Zhong, Yonggang Li, Husheng Dong
Backmatter
Metadaten
Titel
Advanced Image and Video Processing Using MATLAB
verfasst von
Prof. Shengrong Gong
Prof. Chunping Liu
Dr. Yi Ji
Prof. Baojiang Zhong
Yonggang Li
Husheng Dong
Copyright-Jahr
2019
Electronic ISBN
978-3-319-77223-3
Print ISBN
978-3-319-77221-9
DOI
https://doi.org/10.1007/978-3-319-77223-3

Neuer Inhalt

    Bildnachweise