1. Intelligent Vision Systems Image Geometry and Acquisition ENT 496 Ms. HEMA C.R. Lecture 2.

2. 2 Hema-ENT 496- Lecture 2 Road Map  Image Formation  Image Geometry  Image Sampling  Image Quantization  Image Acquisition  Image Definitions

3. 3 Hema-ENT 496- Lecture 2 Image Formation Image formation in the eye and the camera Understanding function of the human eye provides insight into machine vision solutions Biological vision is the process of using light reflected from the surrounding world as a way of modifying behavior

4. 4 Hema-ENT 496- Lecture 2 Image Formation in the eye Light enters through cornea Passes through aqueous humor, the lens and vitreous humor Finally forms an image on the retina Lens adjusts and focus image directly on retina Retina is a complex tiling of photoreceptors known as rods and cones When stimulated by light they produce electrical signals that are transmitted to the brain by the optic nerve Refer: http://homepages/inf.ed.ac.uk/rbf/CVonline/http://homepages/inf.ed.ac.uk/rbf/CVonline/

5. 5 Hema-ENT 496- Lecture 2 Image formation :Pin hole camera Camera is analogous to the eye Pin hole camera has a small hole through which light enters before forming an inverted image Pin hole cameras are modeled by placing image plane between focal point of the camera and the object so that image is not inverted

6. 6 Hema-ENT 496- Lecture 2 Image Geometry Image Formation has two divisions –Geometry of image formation –Physics of light [brightness of point] Image geometry determines where a world point is projected on the image plane

7. 7 Hema-ENT 496- Lecture 2 Image Geometry Object point is represented by x, y and z 3D co-ordinates. Image plane is parallel to x and y axis [world] at a distance f [ focal length ] z x`x` y`y` y (x,y,z) (x`, y`) Object Point f r r` x y

8. 8 Hema-ENT 496- Lecture 2 Image Geometry z x`x` y`y` y (x,y,z) (x`,y`) Object Point f r r` x y Mapping of three dimensions onto two dimension is called perspective projection

9. 9 Hema-ENT 496- Lecture 2 Image Sampling Continuous images are sampled to convert them to digital form Each image sample is called a pixel [picture element] Sampling is the process of representing a continuous signal by a set of samples taken at discrete intervals of time [sampling interval] Continuous Signal Sampled Signal Sampling Frequency

10. 10 Hema-ENT 496- Lecture 2 Original Image Sampled Image Reconstructed Image Image Sampling

11. 11 Hema-ENT 496- Lecture 2 Quantization is the process of converting analog pixel intensities to discrete valued integer numbers Quantization involves assigning a single value to each sample values in such a way that the image reconstructed from quantized values is good Image Quantization

12. 12 Hema-ENT 496- Lecture 2 Image Quantization 550 x 413 pixels 49868 colors 8 colors

13. 13 Hema-ENT 496- Lecture 2 Image Quantization From 600x400, 32 bits image To 600x400, 2 bits image (4 colors) To 600x400, 4 bits image (16 colors)

14. 14 Hema-ENT 496- Lecture 2 Image Acquisition Image acquisition is the first stage of a vision system Acquired Image is dependent on –Nature of sensing device  Vidicon, CCD, infra red, grayscale, color – Properties of the device  Sensitivity, resolution, lenses, stability, focus –The lighting of the scene  Shadows, excessive reflection, poor contrast –The environment  Dust, fog, humidity –The reflective properties of the objects  Texture, color, specularity

15. 15 Hema-ENT 496- Lecture 2 Image Acquisition Acquisition [capture] of 2D Images –Monochrome or Color  Analog Cameras  Digital CCD Cameras  Digital CMOS Cameras  Video Cameras [Analog and Digital]

16. 16 Hema-ENT 496- Lecture 2 Image Capture A basic image capture system contains a lens and a detector. Film detects far more visual information than is possible with a digital system. With digital imaging, the detector is a solid state image sensor called a charge coupled device...CCD for short On an area array CCD, a matrix of hundreds of thousands of microscopic photocells creates pixels by sensing the light intensity of small portions of the image

17. 17 Hema-ENT 496- Lecture 2 Image Capture To capture images in color, red, green and blue filters are placed over the photocells. Film scanners often use three linear array image sensors covered with red, green and blue filters. Each linear image sensor, containing thousands of photocells, is moved across the film to capture the image one-line-at- a-time.

18. 18 Hema-ENT 496- Lecture 2 Image Acquisition Methods of acquisition for 3D –Laser Ranging Systems –Structured Lighting Methods –Moire Fringe Methods –Shape from Shading Methods –Passive Stereoscopic Methods –Active Stereoscopic Methods

19. 19 Hema-ENT 496- Lecture 2 Image Definitions Pixel – A sample of the image intensity quantized to an integer value Image – A two dimensional array of pixels Pixel –Row and column indices [ i, j] are integer values –Pixels have intensity values  0 to 255 grayscale images  RGB value [vector value] color images

20. 20 Hema-ENT 496- Lecture 2 Pixel Array Pixel [4,4] ↓i →j

21. 21 Hema-ENT 496- Lecture 2 Pixel Concept Map

22. 22 Hema-ENT 496- Lecture 2 Pixel The quality of a scanned image is determined by pixel size, or spatial resolution; and by pixel depth, or brightness resolution This relates to the two basic steps in the digital capture process: In step one, sampling determines pixel size and brightness value. In step two quantization determines pixel depth

23. 23 Hema-ENT 496- Lecture 2 Image File Formats Tagged Image Format [.tiff] Portable Network Graphics [.png] Joint Photographic Experts Group [.jpeg,.jpg] Bitmap [.bmp] Graphics Interchange Format [.gif] Raster Images [.ras] Postscript [.ps]

24. End of Lecture 2 Intelligent Vision Systems