Title Details: | |
Image Processing and Analysis |
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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.
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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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