1. CS292 Computational Vision and Language Week 1 - 2

2. 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?

3. Colour image and video sequence colour can be conveyed by combining different colours of light, using three components (red, green and blue): R = r(x,y); G = g(x,y); B = b(x,y), where R, G, B are defined in a similar way to F. The vector (r(x,y), g(x,y), b(x,y)) defines the intensity and colour at the point (x,y) in the colour image. A video sequence is, in effect, a time-sampled representation of the original moving scene. Each frame in the sequence is a standard colour, or monochrome image and can be coded as such. a monochrome video sequence may be represented digitally as a sequence o 2-D arrays [F1, F2, F3..F N ].

4. Java example on image representation and resolution, try this in the lab class

5. Image Resolution How many pixels –spatial resolution How many shades of grey/colours –amplitude resolution How many frames per second –temporal resolution

6. Spatial Resolution n, n/2, n/4, n/8, n/16 and n/32 pixels per unit length

7. amplitude resolution -Shades of Grey 8, 4, 2 and 1 bit images.

8. Temporal Resolution –how much does an object move between frames? –Can motion be understood unambiguously? Nyquist’s Theorem –A periodic signal can be reconstructed if the sampling interval is half the period –An object can be detected if two samples span its smallest dimension

9. Colour Representation three primaries could approximate many colours red, green, blue C= rR+gG+bB Other Colour Models –YMCK –HSI –YCrCb

10. Objectives of vision part Understand the fundamentals in machine perception –Understand components in vision systems –Be familiar with common operations for processing images –Be able to implement simple image processing operations –Be able to implement simple object recognition Evaluate a vision system additionally: encourage the students to practise more basic and advanced Java programming

11. WeeklecturesLabs 1Introduction and simple operations brightness, contrast, enlarge, averaging, subtraction 2 (LP)Image processing and transform 1brightness, contrast, enlarge, averaging, subtraction 3 (LP)Image processing and transform 2Convolution and histogram 4 (LP)Segmentation (1)segmentation 5 (LP)Classification and RecognitionObject recognition 6 (LP)Reading week 7 (LP)Language 1 8 (LP)Language 2 9 (LP)Language 3 10 (LP)Language 4 11revision

12. Deadlines To Undergraduate Office First assignment: week 5, Monday 12th Feb 2007, 12:00noon. Second assignment: week 7, Monday 26th Feb 2007, 12:00noon Third assignment: week 10, Monday 19th March 2007, 12:00noon

13. Assessment Components of Assessment Method(s) weighting Coursework for vision part Program results and short reports 35% Coursework for language part report 15% ExaminationA 2-hour examination (one question on vision, two on language) 50%

14. Recommended Texts Nick Efford, Digital Image Processing, A Practical Introduction using Java (2000), Addison Wesley, ISBN 0201596237. Tim Morris (2004), Computer Vision and Image Processing, Palgrave MacMillan, ISBN 0333994515 Patrick H Winston, (1992), Artificial Intelligence (Third Edition), Addison Wesley Publishers Co. ISBN 0201533774 Rob Callan (2003), Artificial Intelligence, Palgrave MacMillan, ISBN 0333801369 Linda G. Shapiro, George C. Stockman (2001), Computer Vision, Prentice-Hall, Inc, ISBN 0-13-030796-3