Title:

Machine Vision

Code:QA3
Ac.Year:ukončen 2012/2013 (Not opened)
Sem:Winter
Curriculums:
ProgrammeFieldYearDuty
CSE-PHD-4DVI4-Elective
Language of Instruction:Czech
Completion:examination (verbal)
Type of
instruction:
Hour/semLecturesSeminar
Exercises
Laboratory
Exercises
Computer
Exercises
Other
Hours:1300026
 ExamsTestsExercisesLaboratoriesOther
Points:5000050
Guarantor:Honec Jozef, doc. Ing., CSc. (DAME)
Faculty:Faculty of Electrical Engineering and Communication BUT
Department:Department of Control and Instrumentation FEEC BUT
 
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.
Description:
  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.
Knowledge and skills required for the course:
  Rudiments of computer graphics and signal processing.
Subject specific learning outcomes and competencies:
  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 competencies:
  Students will learn about practical approach of application of theoretical knowledge and real application of the knowledge.
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.
 

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