In the following table, you can see a histogram of the hours of content for different topics. The histogram is based on more than 40 courses related to image processing and computer vision from more than 40 universities worldwide.
e.g. 2<X<4 means number of courses between 2 to 4 hours of content
| Subject | X≤2 | 2<X≤4 | 4<X≤6 | X>6 | |
| 1 . | Image Acquisition and Representation | 7 | 5 | 5 | 2 |
| 2 . | Color Image Processing | 11 | 3 | 0 | 0 |
| 3 . | Image Transforms (DFT,DCT,Wavelet,...) | 6 | 6 | 6 | 2 |
| 4 . | Enhancement (Spatial/Frequency Domain) | 6 | 5 | 1 | 2 |
| 5 . | Image Restoration | 1 | 6 | 0 | 1 |
| 6 . | Image Segmentation | 9 | 11 | 0 | 0 |
| 7 . | Edge Detection | 11 | 4 | 2 | 0 |
| 8 . | Other Features Detection (e.g. , corner & contour) | 5 | 4 | 0 | 0 |
| 9 . | Image Registration and Matching | 2 | 1 | 0 | 0 |
| 10 . | Image/ Video Compression | 2 | 1 | 0 | 0 |
| 11 . | Digital Watermarking | 0 | 1 | 0 | 0 |
| 12 . | Image/Video Communication | 1 | 0 | 0 | 0 |
| 13 . | 2D Visual Geometry | 2 | 0 | 0 | 0 |
| 14 . | Stereoscopy & 3D Image Reconstruction | 4 | 3 | 4 | 0 |
| 15 . | Motion Analysis | 5 | 4 | 1 | 0 |
| 16 . | Tracking | 6 | 1 | 1 | 0 |
| 17 . | Object Detection & Recognition | 4 | 5 | 0 | 0 |
| 18 . | Introduction to Pattern Recognition | 2 | 1 | 0 | 1 |
Here you can see more information about course hours and a summary of computer vision, image processing and machine vision course length of 60+ courses from different universities worldwide.
| X is the course length | X≤ 20 hrs | 20<X≤30 hrs | 30<X≤40 hrs | X>40 hrs |
| Number of courses (out of 70) | 11 | 19 | 25 | 8 |
List of Courses |
Total hours (Sessions* hours) |
| 1. Asian Institute of Technology (AIT): Machine Vision for Robotics and HCI (Matthew Dailey) | 48 (16* 3) |
| 2. Bilkent University: Image Analysis (Selim Aksoy) | 50 (28* 1:50') |
| 3. Bonn-Rhein-Sieg University of Applied Sciences: Medical Image Processing (Ing. R. Herpers) | 28 (16* 1:45') |
| 4. Boston University: Image and Video Computing (Margrit Betke) | 36 (24* 1:30') |
| 5. Brown University: Introduction to Computer Vision (Michael J. Black) | 28 (33*0:50') |
| 6. Carnegie Mellon University: Computer Vision (Tai Sing Lee) | 38 (28*1:20') |
| 7. City College of New York: Computer Vision (Zhigang Zhu) | 28 (22* 1:15') |
| 8. Columbia University: Digital Image Processing (Shih-Fu Chang) | 33 (26* 1:15') |
| 9. Cornell University: Computer Vision (A. P. Reeves) | 27 (21* 1:15') |
| 10. CVED: CVed's course lists (Bruce Maxwell) | - |
| 11. Czech Tech. University: 3D Computer Vision (Radim Sara) | 17 (11*1:30') |
| 12. Czech Tech. University: Image Processing, Analysis, and Machine Vision (Vasek Hlavac) | - |
| 13. Czech Tech. University: Lectures in Computer Vision, Image Processing & Analysis (Vasek Hlavac) | - |
| 14. Drexel University: Introduction to Computer Vision (Ko Nishino) | 28 (10* 2:50') |
| 15. Duke University: Introduction to Computer Vision (Carlo Tomasi) | 3 (26* 1:15') |
| 16. Ecole Polytechnique Federale de Lausanne (EPFL): Computer Vision (Pascal Fua) | 35 (20*1:45') |
| 17. Georgia Institute of Technology: Computer Vision (Jim Rehg) | 36 (36* 1) |
| 18. Heriot-Watt University: Image Precessing (Katia Lebart & Yvan Petillot) | 20 (10* 2) |
| 19. Institut de la Francophonie pour l'Informatique (IFI): Traitement d'images (in French) (Alain Boucher) | 15 (5* 3) |
| 20. Institut de la Francophonie pour l'Informatique (IFI): Vision par ordinateur (in French) (Alain Boucher) | 36 (12* 3) |
| 21. Institut Superieur d'Electronique de Paris (ISEP): Digital Image Processing (Florence Rossant) | 30 (20* 1:30') |
| 22. Johns Hopkins University: Computer Vision (Gregory D. Hager) | 32 (25* 1:15') |
| 23. Konstanz University: Digital Image Processing (Dietmar Saupe) | 30 (15* 2) |
| 24. KTH Royal Institute of Technology: Digital Image Processing and Applications (Yifang Ban) | 22 (11* 2) |
| 25. Lehigh University: Image Analysis and Graphics (X. Sharon Huang) | 33 (26* 1:15') |
| 26. Linkoping University: Rotation & Phase Invariant Rep. of Local Image Structures (Michael Felsberg) | 20 (4* 5) |
| 27. Massachusetts Institute of Technology (MIT): Advances in Computer Vision (William T. Freeman) | 38 (25* 1:30') |
| 28. Massachusetts Institute of Technology (MIT): Computer Vision and Applications (Trevor Darrell) | 38 (28* 1:30') |
| 29. Michigan State University: Computer Vision (George Stockman) | 38 (28* 1:20') |
| 30.New York University: Live Image Processing and Performance (R. Luke DuBois) | 35 (14* 2:30') |
| 31. Rensselaer Polytechnic Institute: Cell & Tissue Image Analysis (Badri Roysam) | 32 (24* 1:20') |
| 32. Saarland University: Image Processing and Computer Vision (Bernhard Burgeth) | 62 (31* 2) |
| 33. Sharif University of Technology: Advanced Digital Image Processing (Lecturer) | 45 (30* 1:30') |
| 34. Southern Illinois University: Image Analysis & Computer Vision (Scott E Umbaugh) | 36 (24* 1:30') |
| 35. Stanford University: Digital Image Processing (Bernd Girod) | 18 (21* 0:50') |
| 36. Stanford University: Digital Video Processing (John Apostolopoulos) | 23 (18* 1:15') |
| 37. Tampere University of Technology: Digital Image Processing (Moncef Gabbouj) | 24 (12* 2) |
| 38. Tel Aviv University: Selected Topics in Image Processing (Leonid Yaroslavsky) | 24 (12* 2) |
| 39. Trinity College Dublin: Computer Vision (Kenneth Dawson-Howe & Gerard Lacey) | 32 (32* 1) |
| 40. UC San Diego: Introduction to Computer Vision (David Kriegman) | 27 (20* 1:20') |
| 41. University of Alberta: Introduction to Image Processing (Xiaobo Li) | 24 (28* 0:50') |
| 42. University of Berkeley: Computer Vision (Trevor Darrell) | 38 (25* 1:30') |
| 43. University of Birmingham: Computational Vision (Hamid Dehghani) | 20 (10* 2) |
| 44. University of Cambridge: Computer Vision (John Daugman) | 16 (16* 1) |
| 45. University of Copenhagen: 3D Computer Vision (Adrien Bartoli) | 21 (14*1:30') |
| 46. University of Dundee: Vision & Perception (Stephen McKenna & Manuel Trucco) | 36 (18*2) |
| 47. University of Edinburgh: Advanced Vision (Bob Fisher) | 20 (20* 1) |
| 48. University of Edinburgh: Intro. to Vision & Robotics (Bob Fisher & Michael Herrmann) | 16 (16*1) |
| 49. University of Felorida: Image Processing and Computer Vision (Dapeng Wu) | 35 (42* 0:50') |
| 50. University of Geneva: Advanced Image Processing (Sviatoslav Voloshynovskiy) | 25 (14* 1:45') |
| 51. University of Illinois: Image Processing (Minh N. Do) | 38 (28* 1:20') |
| 52. University of Manchester: Advanced Machine Vision (A. Galata) | 40 (5* 8) |
| 53. University of Minnesota: Computer Vision (Nikolaos Papanikolopoulos) | 38 (30*1:15') |
| 54. University of Nevada, Reno: Computer Vision (George Bebis) | 39 (31* 1:15') |
| 55. University of New South Wales: Computer Vision (Arcot Sowmya) | 42 (14* 3) |
| 56. University of New South Wales: Computer Vision (Du Huynh) | 26 (13* 2) |
| 57. University of North Carolina: Computer Vision (Svetlana Lazebnik) | 36 (29* 1:15') |
| 58. University of Otago: Computer Vision (Brendan McCane) | - |
| 59. University of Ottawa: Image Processing and Image Communication (Eric Dubois) | 24 (16* 1:30') |
| 60. University of Oulu: Digital Image Processing (Matti Pietikainen) | 42 (21* 2) |
| 61. University of Sussex: Advanced Computer Vision (David Young) | 14 (16* 0:50') |
| 62. University of Texas at Austin: Special Topics in Computer Vision (Kristen Grauman) | 42 (14* 3) |
| 63. University of Toronto: Topics in Vision: Visual Motion Analysis (David Fleet & Allan Jepson) | 24 (12* 2) |
| 64. University of Washington: Computer Vision (Clark F. Olson) | 42 (20* 2:05) |
| 65. University of Western Australia: Computer Vision (Du Huynh) | 26 (13* 2) |
| 66. University of Wisconsin: Computer Vision (Chuck Dyer) | 19 (15: 1:30') |
| 67. Yale University: Computational Vision and Biological Perception (Steven W. Zucker) | 36 (24*1:30') |
© 2010 Robert Fisher