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Title Details:
Image Processing and Analysis
Authors: Tziritas, Georgios
Komontakis, Nikos
Subject: MATHEMATICS AND COMPUTER SCIENCE > COMPUTER SCIENCE > COMPUTATIONAL SCIENCE > PROCESSING
MATHEMATICS AND COMPUTER SCIENCE > COMPUTER SCIENCE > COMPUTATIONAL SCIENCE > DATA, INFORMATION AND KNOWLEDGE
MATHEMATICS AND COMPUTER SCIENCE > COMPUTER SCIENCE > INTELLIGENT SYSTEMS > BASIC MACHINE LEARNING
MATHEMATICS AND COMPUTER SCIENCE > COMPUTER SCIENCE > INTELLIGENT SYSTEMS > ADVANCED MACHINE LEARNING
MATHEMATICS AND COMPUTER SCIENCE > COMPUTER SCIENCE > INTELLIGENT SYSTEMS > PERCEPTION AND COMPUTER VISION
ENGINEERING AND TECHNOLOGY > TECHNOLOGICAL SCIENCES AND ENGINEERING > TELECOMMUNICATIONS ENGINEERING AND TECHNOLOGY > SIGNALS AND SYSTEMS
ENGINEERING AND TECHNOLOGY > TECHNOLOGICAL SCIENCES AND ENGINEERING > TELECOMMUNICATIONS ENGINEERING AND TECHNOLOGY > STOCHASTIC PROCESSES - NOISE
Keywords:
Principal component analysis
Scale space representation
Edge detection
Corner detection
Image matching
Image restoration
Image enhancement
Discrete Fourier transform
Discrete cosine transform
Image binarization
Active contours
Feature extraction
Histogram equalization
Regularization theory
Quantization
Wavelet transform
JPEG coding
Mathematical morphology
Image denoising
Fourier transform
Hough transform
Mixture models
Image content description
Covariance matrix
Image compression
Convolutional neural networks
Convolution
Image classification
Image segmentation
Graph cuts
Markov random fields
Image texture
Median filters
Gabor filters
Wiener filters
Color systems
Spatial filters
Image digitization
Description:
Abstract:
The main objectives of the book are to introduce the fundamental concepts and methodologies applied in image processing and analysis and to provide solid knowledge that can be the basis for further study and research in this field. The entire fundamental topics of image processing and analysis are covered, starting from the basic characteristics of images, their digitization, image enhancement by pixel-based processing, as well as spatial filtering or in the frequency domain. Also, the book includes orthogonal transformations with emphasis on the Fourier transform, cosine transform and principal component analysis, as well as wavelet transform. We refer to filtering to smooth images, including noise reduction. Image restoration methods are presented concerning regularization theory. We further focus on the basic methodologies and techniques of morphological processing. A thorough discussion of image compression techniques is given with a detailed presentation of coding schemes and standards. The localization of image region contours through edge detection and tracking of active contours in level sets is presented in detail. A comprehensive report on image segmentation is given, using both classical methods and Markov random field models, graph cuts and level sets. Corner detection and feature extraction are considered and are also used in the content description, which also includes statistical and geometric features. Matching images based on feature points or dense fields is presented in detail. Finally, an extensive introduction to neural networks and deep learning is included with a focus on convolutional neural networks.
Linguistic Editors: Tikopoulou, Magda
Technical Editors: Karatzidis, Dimitrios
Graphic Editors: Tziritas, Georgios
Type: Undergraduate textbook
Creation Date: 06-06-2023
Item Details:
ISBN 978-618-228-013-3
License: Attribution - NonCommercial - ShareAlike 4.0 International (CC BY-NC-SA 4.0)
DOI http://dx.doi.org/10.57713/kallipos-243
Handle http://hdl.handle.net/11419/9695
Bibliographic Reference: Tziritas, G., & Komontakis, N. (2023). Image Processing and Analysis [Undergraduate textbook]. Kallipos, Open Academic Editions. https://dx.doi.org/10.57713/kallipos-243
Language: Greek
Consists of:
1. Introduction
2. Basic image features
3. Two-dimensional continuous signals and digitization
4. Pixel-based image processing
5. Spatial image processing
6. Orthogonal transforms
7. Wavelet analysis
8. Noise reduction and image smoothing
9. Morphological image processing
10. Image restoration
11. Image compression
12. Edge detection and contour localization
13. Image segmentation
14. Detection of feature points and regions
15. Image content description
16. Image matching
17. Convolutional neural networks
Additional Material
Number of pages 520
Publication Origin: Kallipos, Open Academic Editions
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