Book description
Emerging Trends in Image Processing, Computer Vision, and Pattern Recognition discusses the latest in trends in imaging science which at its core consists of three intertwined computer science fields, namely: Image Processing, Computer Vision, and Pattern Recognition. There is significant renewed interest in each of these three fields fueled by Big Data and Data Analytic initiatives including but not limited to; applications as diverse as computational biology, biometrics, biomedical imaging, robotics, security, and knowledge engineering. These three core topics discussed here provide a solid introduction to image processing along with low-level processing techniques, computer vision fundamentals along with examples of applied applications and pattern recognition algorithms and methodologies that will be of value to the image processing and computer vision research communities.
Drawing upon the knowledge of recognized experts with years of practical experience and discussing new and novel applications Editors’ Leonidas Deligiannidis and Hamid Arabnia cover;
- Many perspectives of image processing spanning from fundamental mathematical theory and sampling, to image representation and reconstruction, filtering in spatial and frequency domain, geometrical transformations, and image restoration and segmentation
- Key application techniques in computer vision some of which are camera networks and vision, image feature extraction, face and gesture recognition and biometric authentication
- Pattern recognition algorithms including but not limited to; Supervised and unsupervised classification algorithms, Ensemble learning algorithms, and parsing algorithms.
- How to use image processing and visualization to analyze big data.
- Discusses novel applications that can benefit from image processing, computer vision and pattern recognition such as computational biology, biometrics, biomedical imaging, robotics, security, and knowledge engineering.
- Covers key application techniques in computer vision from fundamentals to mid to high level processing some of which are camera networks and vision, image feature extraction, face and gesture recognition and biometric authentication.
- Presents a number of pattern recognition algorithms and methodologies including but not limited to; supervised and unsupervised classification algorithms, Ensemble learning algorithms, and parsing algorithms.
- Explains how to use image processing and visualization to analyze big data.
Table of contents
- Cover image
- Title page
- Table of Contents
- Copyright
- Contributors
- Acknowledgments
- Preface
- Introduction
-
Part 1: Image and Signal Processing
- Chapter 1: Denoising camera data: Shape-adaptive noise reduction for color filter array image data
- Chapter 2: An approach to classifying four-part music in multidimensional space
- Chapter 3: Measuring rainbow trout by using simple statistics
- Chapter 4: Fringe noise removal of retinal fundus images using trimming regions
- Chapter 5: pSQ: Image quantizer based on contrast band-pass filtering
- Chapter 6: Rebuilding IVUS images from raw data of the RF signal exported by IVUS equipment
- Chapter 7: XSET: Image coder based on contrast band-pass filtering
- Chapter 8: Security surveillance applications utilizing parallel video-processing techniques in the spatial domain
- Chapter 9: Highlight image filter significantly improves optical character recognition on text images
- Chapter 10: A study on the relationship between depth map quality and stereoscopic image quality using upsampled depth maps
- Chapter 11: ρGBbBShift: Method for introducing perceptual criteria to region of interest coding
- Chapter 12: DT-Binarize: A decision tree based binarization for protein crystal images
- Chapter 13: Automatic mass segmentation method in mammograms based on improved VFC snake model
- Chapter 14: Correction of intensity nonuniformity in breast MR images
- Chapter 15: Traffic control by digital imaging cameras
- Chapter 16: Night color image enhancement via statistical law and retinex
-
Part 2: Computer Vision and Recognition Systems
- Chapter 17: Trajectory evaluation and behavioral scoring using JAABA in a noisy system
- Chapter 18: An algorithm for mobile vision-based localization of skewed nutrition labels that maximizes specificity
- Chapter 19: A rough fuzzy neural network approach for robust face detection and tracking
- Chapter 20: A content-based image retrieval approach based on document queries
- Chapter 21: Optical flow-based representation for video action detection
- Chapter 22: Anecdotes extraction from webpage context as image annotation
- Chapter 23: Automatic estimation of a resected liver region using a tumor domination ratio
- Chapter 24: Gesture recognition in cooking video based on image features and motion features using Bayesian network classifier
- Chapter 25: Biometric analysis for finger vein data: Two-dimensional kernel principal component analysis
- Chapter 26: A local feature-based facial expression recognition system from depth video
- Chapter 27: Automatic classification of protein crystal images
- Chapter 28: Semi-automatic teeth segmentation in 3D models of dental casts using a hybrid methodology
- Chapter 29: Effective finger vein-based authentication: Kernel principal component analysis
- Chapter 30: Detecting distorted and benign blood cells using the Hough transform based on neural networks and decision trees
-
Part 3: Registration, Matching, and Pattern Recognition
- Chapter 31: Improving performance with different length templates using both of correlation and absolute difference on similar play estimation
- Chapter 32: Surface registration by markers guided nonrigid iterative closest points algorithm
- Chapter 33: An affine shape constraint for geometric active contours
- Chapter 34: A topological approach for detection of chessboard patterns for camera calibration
- Chapter 35: Precision distortion correction technique based on FOV model for wide-angle cameras in automotive sector
- Chapter 36: Distances and kernels based on cumulative distribution functions
- Chapter 37: Practical issues for binary code pattern unwrapping in fringe projection method
- Chapter 38: Detection and matching of object using proposed signature
- Index
Product information
- Title: Emerging Trends in Image Processing, Computer Vision and Pattern Recognition
- Author(s):
- Release date: December 2014
- Publisher(s): Morgan Kaufmann
- ISBN: 9780128020920
You might also like
book
Microscope Image Processing
Digital image processing, an integral part of microscopy, is increasingly important to the fields of medicine …
book
Adaptive Learning Methods for Nonlinear System Modeling
Adaptive Learning Methods for Nonlinear System Modeling presents some of the recent advances on adaptive algorithms …
book
Lossless Information Hiding in Images
Lossless Information Hiding in Images introduces many state-of-the-art lossless hiding schemes, most of which come from …
book
Academic Press Library in Signal Processing
This third volume of a five volume set, edited and authored by world leading experts, gives …