DELETED: Machine VisionLaajuus (5 cr)

Objective

Upon completion of the course the student 1. understands the fundamentals of image acquisition, representation and modeling 2. can utilize elementary methods of machine vision for image recognition problems 3. can use 2D transformations in model fitting and image registration 4. can explain the basics of 3D imaging and reconstruction

Content

1. Introduction, 2. Imaging and image representations, 3. Light and color, 4. Binary image analysis, 5. Texture, 6. Local features, 7. Recognition, 8. Motion, 9. 2D models and transformations, 10. Perceiving 3D from 2D images, 11. 3D transformations and reconstruction.

Qualifications

Recommended prior courses: 521467A Digital Image Processing or an equivalent course, 521141P Elementary Programming or an equivalent course providing basic Python programming skills

Assessment criteria, satisfactory (1)

The grading is based on points collected from exams and homework assignments. More specific criteria are published in Moodle.

Materials

Video lectures and slides, exercise material, Jupyter notebook guides and tutorials, OpenCV documentation and tutorials, and code examples.

Execution methods

The course contains lectures (22 h), exercises (16 h), programming assignments (32 h), and self-studying (63 h). Lectures and exercises include in-class quizzes that enable passing the course without a final exam. Mode of delivery: blended teaching.

Accomplishment methods

The course is completed with exams (in-class quizzes or a final exam) and homework assignments.