1. Top 10 Guardian League Table for Computer Sciences and IT Top 10 Times Online League Table for Computer Science Computer’s Eye

2. Part 1. Introduction to computer vision and image processing (40 minutes) Break (10 minutes) Part 2. Hands-on image processing (45 minutes)

3. Computational Perception? Human Perceptual Modalities –Tactile – touch –Gustatory – taste –Visual – sight –Auditory – hearing –Olfactory – smell Perception is the process by which the information from our senses is perceived by us. Computer Vision is the science and technology of machines that see.

4. Robotics/industry inspection /military

5. Police surveillance, genome research, biometrics, security

6. Remote sensing, astronomy, GIS, Earth/Planetary observation, monitoring, exploration

7. Medical imaging

8. Aware home / Intelligent environments, ubiquitous computing/sensing /eldercare technologies

9. Digital special effects film and TV, DTV, news and sport, creative media, art, museums

10. Taking the human visual system for granted One of the ultimate challenges of machine vision is getting a machine to recognise objects in the world. The subtlety and difficulty of describing the exact operation of the subconscious functions presents significant difficulty in developing algorithms to emulate human visual behaviour

12. Visual Perception The main focus will be on the processing of the raw information that they provide. The basic approach : understand how sensory stimuli are created by the world, and then ask what must the world have been like to produce this particular stimulus?

13. Image and pixels

14. x n 0 m y f(x,y) A digital image consisting of an array of m x n pixels in the x th column and the y th row has an intensity equal to f(x,y). (r(x,y), g(x,y), b(x,y))

16. Vision System Overview Feature Extraction, representation of properties Labels or other forms of description Pre-processing, enhancement Object classification and Recognition Image classification and Recognition Captured data Knowledge representation

17. Feature Extraction, representation of properties

18. Image Analysis Common image analysis techniques include template matching, pattern recognition using feature extraction

19. Classification, recognition and retrieval

20. How are we going to manipulate images today?

21. Brightness Adjustment Add a constant to all values g(x,y) = f(x,y) + k Where f is the original images and g the changed image; k is a constant, i.e.,50

22. Contrast Adjustment Scale all values by a constant g(x,y) = a* f(x,y) (a = 1.5)

23. Subtraction

24. Average of two images