School of Computing

Module details

EL844 Fundamentals of Image Analysis (15 credits)

Syllabus

Fundamentals of image analysis provides an introduction to the principles of identity authentication based on biometrics and introduces the fundamental underlying theoretical and practical skills required for their development.

  • Fundamentals of Image Processing
    General introduction to digital image processing; image acquisition, quantisation and representation; Affine transforms; image enhancement techniques: contrast manipulation, binarisation, noise removal (spatial and frequency domain); edge detection techniques; image segmentation: edge-based, region-based, watershed; Hough transform; image feature extraction; advanced image processing: morphological operations, colour image processing, various image transforms (Fourier, wavelet, etc).
  • Fundamentals of Pattern Recognition
    Patterns and pattern classification, and the role of classification in a variety of application scenarios, including security and biometrics. Basic concepts: pattern descriptors, pattern classes; invariance and normalisation. Feature-based analysis. Texture analysis. The classification problem and formal approaches. Basic decision theory and the Bayesian classifier. Cost and risk and their relationship; rejection margin and error-rate trade-off. Canonical forms of classifier description. Estimation of class-conditional distributions; bivariate and multivariate analysis. Euclidean and Mahalanobis distance metrics and minimum distance classifiers. Parametric and non-parametric classification strategies. Linear discriminant analysis. Clustering approaches, and relationship between classifier realisations. Practical case studies.
  • Implementation essentials
    Programming and data analysis using MATLAB and other software tools as appropriate. Introduction to practical work using MATLAB.

This module is delivered by the School of Engineering and Digital Arts.

Note

This web page provides advance information about a module due to run in the coming academic year. We believe the details are accurate at the time of writing but they may be subject to change.

School of Computing, University of Kent, Canterbury, Kent, CT2 7NF

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Last Updated: 24/09/2010 15:17