Faculty of Information Technology, BUT

Course details

Machine Vision

QA3 Acad. year 2007/2008 Winter semester

Image acquisition, technical means and their application possibilities. Scene illumination. Means of acquisition and processing of image, signal processors. Synchronization of acquisition and processing with technological processes. Preparations of experiments, mathematical and software processing of the acquired data sets. Reproducibility of the results in real use. Additional notes for image processing.

Guarantor

Honec Jozef, doc. Ing., CSc. (DAME FEEC BUT)

Language of instruction

Czech

Completion

Examination (oral)

Time span

13 hrs lectures, 26 hrs projects

Assessment points

50 exam, 50 projects

Department

Lecturer

Honec Jozef, doc. Ing., CSc. (DAME FEEC BUT)

Subject specific learning outcomes and competences

To get acquainted with possibilities and limitations of application of image processing and computer vision. To learn theoretical knowledge about computer vision and their application in selected technical and industrial tasks. To get acquainted with solutions of projects in the industry, traffic, and state offices. To learn to participate on real solutions in teams.

Generic learning outcomes and competences

Students will learn about practical approach of application of theoretical knowledge and real application of the knowledge.

Learning objectives

To get acquainted with possibilities and limitations of application of image processing and computer vision. To learn theoretical knowledge about computer vision and their application in selected technical and industrial tasks. To get acquainted with solutions of projects in the industry, traffic, and state offices. To learn to participate on real solutions in teams.

Prerequisite kwnowledge and skills

Rudiments of computer graphics and signal processing.

Syllabus of lectures

  1. Introduction, image acquisition.
  2. Hardware and its limitations.
  3. Scene illumination design.
  4. Means of image acquisition.
  5. Means of image processing.
  6. Signal processors.
  7. Synchronization of image acquisition with technological process.
  8. Experiment preparation.
  9. Mathematical fundamentals of experiments.
  10. Experimental software.
  11. Experimental data processing.
  12. Reproducibility of results in reality.
  13. Further visual systems remarks.

Syllabus - others, projects and individual work of students

  • Individually assigned project for the whole duration of the course.

Progress assessment

Submitting of projects.

Course inclusion in study plans

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