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Emerging Trends in Image Processing, Computer Vision and Pattern Recognition

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

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Copyright
  5. Contributors
  6. Acknowledgments
  7. Preface
  8. Introduction
  9. Part 1: Image and Signal Processing
    1. Chapter 1: Denoising camera data: Shape-adaptive noise reduction for color filter array image data
      1. Abstract
      2. 1 Introduction
      3. 2 Camera noise
      4. 3 Adaptive raw data denoising
      5. 4 Experiments: Image quality vs system performance
      6. 5 Video Sequences
      7. 6 Conclusion
    2. Chapter 2: An approach to classifying four-part music in multidimensional space
      1. Abstract
      2. 1 Introduction
      3. 2 Collecting the pieces<span xmlns="http://www.w3.org/1999/xhtml" xmlns:epub="http://www.idpf.org/2007/ops" class="italic"><span class="bold">&#8212;</span></span>training and test piecestraining and test pieces
      4. 3 Parsing musicXML<span xmlns="http://www.w3.org/1999/xhtml" xmlns:epub="http://www.idpf.org/2007/ops" class="italic"><span class="bold">&#8212;</span></span>training and test piecestraining and test pieces
      5. 4 Collecting Piece Statistics
      6. 5 Collecting Classifier Statistics<span xmlns="http://www.w3.org/1999/xhtml" xmlns:epub="http://www.idpf.org/2007/ops" class="italic"><span class="bold">&#8212;</span></span>Training Pieces OnlyTraining Pieces Only
      7. 6 Classifying Test Pieces
      8. 7 Additional Composer and Metrics
      9. 8 Conclusions
    3. Chapter 3: Measuring rainbow trout by using simple statistics
      1. Abstract
      2. Acknowledgments
      3. 1 Introduction
      4. 2 Experimental prototype
      5. 3 Statistical Measuring Approach
      6. 4 Experimental framework
      7. 5 Performance evaluation
      8. 6 Conclusions
    4. Chapter 4: Fringe noise removal of retinal fundus images using trimming regions
      1. Abstract
      2. 1 Introduction
      3. 2 Methodology
      4. 3 Results and Discussion
      5. 4 Conclusion
    5. Chapter 5: pSQ: Image quantizer based on contrast band-pass filtering
      1. Abstract
      2. Acknowledgment
      3. 1 Introduction
      4. 2 Related Work: JPEG 2000 Global Visual Frequency Weighting
      5. 3 Perceptual quantization
      6. 4 Experimental results
      7. 5 Conclusions
    6. Chapter 6: Rebuilding IVUS images from raw data of the RF signal exported by IVUS equipment
      1. Abstract
      2. Acknowledgments
      3. 1 Introduction
      4. 2 Method for IVUS image reconstruction
      5. 3 Experimental results
      6. 4 Discussion, conclusion, and future work
    7. Chapter 7: XSET: Image coder based on contrast band-pass filtering
      1. Abstract
      2. Acknowledgment
      3. 1 Introduction
      4. 2 Related Work: JPEG2000 Global Visual Frequency Weighting
      5. 3 Image entropy encoding: XSET algorithm
      6. 4 Experiments and results
      7. 5 Conclusions
    8. Chapter 8: Security surveillance applications utilizing parallel video-processing techniques in the spatial domain
      1. Abstract
      2. Acknowledgments
      3. 1 Introduction
      4. 2 Graphical Processing Unit and Compute Unified Device Architecture
      5. 3 Parallel algorithms for image processing
      6. 4 Applications for surveillance using parallel video processing
      7. 5 Conclusion
    9. Chapter 9: Highlight image filter significantly improves optical character recognition on text images
      1. Abstract
      2. 1 Introduction
      3. 2 Description of smart contrast image filter
      4. 3 Description of highlight image filter
      5. 4 Description of the optimized implementation of smart contrast and highlight Using “Byte Buffer” Techniques
      6. 5 Conclusions
    10. Chapter 10: A study on the relationship between depth map quality and stereoscopic image quality using upsampled depth maps
      1. Abstract
      2. 1 Introduction
      3. 2 Objective quality assessment tools
      4. 3 3D Subjective Quality Assessment
      5. 4 Experimental results
      6. 5 Conclusion
    11. Chapter 11: ρGBbBShift: Method for introducing perceptual criteria to region of interest coding
      1. Abstract
      2. ACKNOWLEDGMENT
      3. 1 Introduction
      4. 2 Related work
      5. 3 Perceptual GBbBShift
      6. 4 Experimental results
      7. 5 Conclusions
    12. Chapter 12: DT-Binarize: A decision tree based binarization for protein crystal images
      1. Abstract
      2. Acknowledgment
      3. 1 Introduction
      4. 2 Background
      5. 3 DT-Binarize: Selection of best binarization method using decision tree
      6. 4 Experiments and results
      7. 5 Conclusion
    13. Chapter 13: Automatic mass segmentation method in mammograms based on improved VFC snake model
      1. Abstract
      2. Acknowledgments
      3. 1 Introduction
      4. 2 Methodology
      5. 3 Experiment results and discussion
      6. 4 Conclusions
    14. Chapter 14: Correction of intensity nonuniformity in breast MR images
      1. Abstract
      2. Acknowledgments
      3. 1 Introduction
      4. 2 Preprocessing steps
      5. 3 Experimental Results
      6. 4 Conclusion
    15. Chapter 15: Traffic control by digital imaging cameras
      1. Abstract
      2. 1 Introduction
      3. 2 Paper Overview
      4. 3 Implementation
      5. 4 Traffic detectors
      6. 5 Image processing
      7. 6 Project design
      8. 7 Performance analysis
      9. 8 General Conclusion
    16. Chapter 16: Night color image enhancement via statistical law and retinex
      1. Abstract
      2. 1 Introduction
      3. 2 Overview of Retinex Theory
      4. 3 Analyzing the transformation law and enhancing the nighttime image
      5. 4 Comparison and results
      6. 5 Application
      7. 6 The conclusion
  10. Part 2: Computer Vision and Recognition Systems
    1. Chapter 17: Trajectory evaluation and behavioral scoring using JAABA in a noisy system
      1. Abstract
      2. Acknowledgments
      3. 1 Introduction
      4. 2 Methods
      5. 3 Results
      6. 4 Discussion
    2. Chapter 18: An algorithm for mobile vision-based localization of skewed nutrition labels that maximizes specificity
      1. Abstract
      2. 1 Introduction
      3. 2 Previous work
      4. 3 Skewed NL localization
      5. 4 Experiments
      6. 5 Conclusions
    3. Chapter 19: A rough fuzzy neural network approach for robust face detection and tracking
      1. Abstract
      2. Acknowledgments
      3. 1 Introduction
      4. 2 Theoretical background
      5. 3 Face-detection method
      6. 4 Skin Map Segmentation
      7. 5 Face detection
      8. 6 Face Tracking
      9. 7 Experiments
      10. 8 Conclusions and Future Works
    4. Chapter 20: A content-based image retrieval approach based on document queries
      1. Abstract
      2. Acknowledgments
      3. 1 Introduction
      4. 2 Related Work
      5. 3 Our approach
      6. 4 Experimental setup
      7. 5 Future research
    5. Chapter 21: Optical flow-based representation for video action detection
      1. Abstract
      2. 1 Introduction
      3. 2 Related work
      4. 3 Temporal segment representation
      5. 4 Optical flow
      6. 5 Optical flow-based segment representation
      7. 6 Cut Detection Inspiration
      8. 7 Experiments and results
      9. 8 Conclusion
    6. Chapter 22: Anecdotes extraction from webpage context as image annotation
      1. Abstract
      2. Acknowledgments
      3. 1 Introduction
      4. 2 Literature background
      5. 3 Research design
      6. 4 Evaluation
      7. 5 Conclusion
    7. Chapter 23: Automatic estimation of a resected liver region using a tumor domination ratio
      1. Abstract
      2. 1 Introduction
      3. 2 Estimating an ideal resected region using the TDR
      4. 3 Estimating an Optimal Resected Region Under the Practical Conditions in Surgery
      5. 4 Modifying a Resected Region Considering Hepatic Veins
      6. 5 Conclusion
    8. Chapter 24: Gesture recognition in cooking video based on image features and motion features using Bayesian network classifier
      1. Abstract
      2. Acknowledgments
      3. 1 Introduction
      4. 2 Related work
      5. 3 Our Method
      6. 4 Experiments
      7. 5 Conclusions
    9. Chapter 25: Biometric analysis for finger vein data: Two-dimensional kernel principal component analysis
      1. Abstract
      2. 1 Introduction
      3. 2 Image Acquisition
      4. 3 Two-dimensional principal component analysis
      5. 4 Kernel mapping along row and column direction
      6. 5 Finger Vein Recognition Algorithm
      7. 6 Experimental results on finger vein database
      8. 7 Conclusion
    10. Chapter 26: A local feature-based facial expression recognition system from depth video
      1. Abstract
      2. ACKNOWLEDGEMENT
      3. 1 Introduction
      4. 2 Depth Image Preprocessing
      5. 3 Feature extraction
      6. 4 Experiments and results
      7. 5 Concluding Remarks
    11. Chapter 27: Automatic classification of protein crystal images
      1. Abstract
      2. Acknowledgment
      3. 1 Introduction
      4. 2 Image Categories
      5. 3 System overview
      6. 4 Image preprocessing and feature extraction
      7. 5 Experimental results
      8. 6 Conclusion and Future Work
    12. Chapter 28: Semi-automatic teeth segmentation in 3D models of dental casts using a hybrid methodology
      1. Abstract
      2. Acknowledgments
      3. 1 Introduction
      4. 2 Dental Study Model
      5. 3 Point cloud segmentation
      6. 4 Results of segmentation techniques applied to 3D dental models
      7. 5 Comments and Discussions
      8. 6 Conclusion
    13. Chapter 29: Effective finger vein-based authentication: Kernel principal component analysis
      1. Abstract
      2. 1 Introduction
      3. 2 Image Acquisition
      4. 3 Principal component analysis
      5. 4 Kernel principal component analysis
      6. 5 Experimental results
      7. 6 Conclusion
    14. Chapter 30: Detecting distorted and benign blood cells using the Hough transform based on neural networks and decision trees
      1. Abstract
      2. 1 Introduction
      3. 2 Related work
      4. 3 Hough transforms
      5. 4 Overview of NN
      6. 5 Overview of the classification and regression tree
      7. 6 The proposed algorithm
      8. 7 The experimental results
      9. 8 Conclusions
  11. Part 3: Registration, Matching, and Pattern Recognition
    1. Chapter 31: Improving performance with different length templates using both of correlation and absolute difference on similar play estimation
      1. Abstract
      2. 1 Introduction
      3. 2 Structure of the proposed method
      4. 3 1D degeneration from videos
      5. 4 Similarity Measure with Correlation and Absolute Difference in Motion Retrieving Method
      6. 5 Experiments on baseball games and evaluations
      7. 6 Conclusions
    2. Chapter 32: Surface registration by markers guided nonrigid iterative closest points algorithm
      1. Abstract
      2. Acknowledgment
      3. 1 Introduction
      4. 2 Materials and methods
      5. 3 Results
      6. 4 Discussion and conclusions
    3. Chapter 33: An affine shape constraint for geometric active contours
      1. Abstract
      2. 1 Introduction
      3. 2 Shape alignment using fourier descriptors
      4. 3 Shape Prior for Geometric Active Contours
      5. 4 Experimental results
      6. 5 Conclusions
    4. Chapter 34: A topological approach for detection of chessboard patterns for camera calibration
      1. Abstract
      2. 1 Introduction
      3. 2 X-corner detector
      4. 3 Topological filter
      5. 4 Point Correspondences
      6. 5 Location refinement
      7. 6 Experimental Results
      8. 7 Conclusions
    5. Chapter 35: Precision distortion correction technique based on FOV model for wide-angle cameras in automotive sector
      1. Abstract
      2. Acknowledgments
      3. 1 Introduction
      4. 2 Related research
      5. 3 Distortion center estimation method using FOV model and 2D patterns
      6. 4 Experiment and evaluation
      7. 5 Application of algorithm to products improving vehicle convenience
      8. 6 Conclusion
    6. Chapter 36: Distances and kernels based on cumulative distribution functions
      1. Abstract
      2. 1 Introduction
      3. 2 Distance and Similarity Measures Between Distributions
      4. 3 Distances on cumulative distribution functions
      5. 4 Experimental results and discussions
      6. 5 Generalization
      7. 6 Conclusions and Future Work
    7. Chapter 37: Practical issues for binary code pattern unwrapping in fringe projection method
      1. Abstract
      2. 1 Introduction
      3. 2 Prior and related work
      4. 3 Practical issues for fringe pattern generation
      5. 4 Binary code generation for phase ambiguity resolution
      6. 5 Practical issues for projected fringe pattern photography
      7. 6 Three-dimensional reconstruction
      8. 7 Summary and conclusions
    8. Chapter 38: Detection and matching of object using proposed signature
      1. Abstract
      2. 1 Introduction
      3. 2 Overview on SURF method
      4. 3 Overview on Image Segmentation
      5. 4 The proposed algorithm
      6. 5 Experimental results
      7. 6 Conclusions
  12. Index