DD2427 Image Based Recognition and Classification 6.0 credits

Bildbaserad igenkänning och klassificering

A course in computer science focusing on basic theory, models, and methods for classification of data with special emphasis on object recognition in digital images.

Academic level (A-D) D Subject area
Educational level 2 Grade scale A, B, C, D, E, FX, F

Spring 10 bik10 for programme students

Periods 4 (6.0 cr) Application code 80369
Start date End date
Language of instruction English Campus KTH Campus
Course pace 100% Tutoring time Daytime
Number of places Form of study NML
Course responsible
Teacher
Target group

All who have the required prior knowledge

Goals

After the course you should be able to:

  • identify basic notions, terminology, theories models and methods for classification of data,
  • develop and systematically evaluate a number of basic methods for classification of data,
  • experimentally evaluate algorithms for classification and recognition of objects in digital gray value images,
  • choose appropriate method in order to automatically solve a given classification problem,
  • know about theories of how the brain processes visual information for classification,

in order to

  • be able to solve general problems of data representation and classification,
  • be able to implement, analyze and evaluate simple systems for automatic classification of images,
  • obtain a broad base of knowledge in order to be able to acquire information about and read literature in the field.

Content

  • Representation and feature extraction in digital images
  • principles of recognition and classification, Bayesian decisions
  • discriminant functions, neural networks, support vector machines
  • learning, optimization of classifiers
  • overview of recognition in biological systems
  • examples of recognition: handwritten text, faces, objects.

Eligibility

Prerequisites

Knowledge corresponding to the compulsory courses on mathematics, computer science and numerical analysis on D-, E- or F-programme.

Literature

Material produced at the department.

Examination

  • INL1 - Assignment, 1.5 credits, grade scale: P, F
  • LAB1 - Laboratory Work, 1.5 credits, grade scale: P, F
  • TEN1 - Examination, 3.0 credits, grade scale: A, B, C, D, E, FX, F

In this course all the regulations of the code of honor at the School of Computer science and Communication apply, see: http://www.kth.se/csc/student/hederskodex/1.17237?l=en_UK.

Requirements for final grade

Laboratory assignments (LAB1; 1,5 university credits)
Hand in exercise (INL1; 1,5 university credits)
Examination (TEN1; 3 university credits )

Offered by

CSC/Computer Science

Contact

Josephine Sullivan, tel: 790 6136, e-post: sullivan@nada.kth.se

Examiner

Ordinarie examinator är Stefan Carlsson.

Add-on studies

Discuss with course leader.

Version

Course plan valid from: Autumn 09.

Print Last updated: 2009-11-02