1 / 27

Image Processing Lecture 2

Image Processing Lecture 2. Gaurav Gupta Shobhit Niranjan. Today. Image Formation (More Details) Camera Models Perspective Geometry Color Models. Human Visual System (HVS): The Eye. Image is formed on retina Photoreceptors (rods and cones) are stimulated and generate visual signal

yazid
Download Presentation

Image Processing Lecture 2

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Image Processing Lecture 2 Gaurav Gupta Shobhit Niranjan

  2. Today • Image Formation (More Details) • Camera Models • Perspective Geometry • Color Models

  3. Human Visual System (HVS): The Eye • Image is formed on retina • Photoreceptors (rods and cones) are stimulated and generate visual signal • Received and processed by brain (Cortex)

  4. Pin Hole Camera Model • Light enters through small hole. • Image plane is placed between focal point and object (to have “non-inverted” projection)

  5. Perspective Geometry • Mapping from R3->R2 • Convention image coordinate (u,v), object coordinate (x,y,z) u = (f/z)x ; v = (f/z)y f = focal length (by geometry) The linear version is ( S = scale factor)

  6. Contd.. • Concept of Vanishing Line, Point and Horizon is important for Reconstruction from 2D image to 3D information • Vanishing point : The point where parallel lines at particular direction meet . • Two sets of parallel lines in different directions will give two vanishing points. • Two vanishing points form a vanishing line for the collection of parallel planes defined by these two sets of parallel lines.

  7. The Horizon • Vanishing Line for ground plane • Anything below it will be below horizon and above it will be above horizon • Different heights of viewer ?? What would be affect on the horizon?

  8. Interpretation of Calibration matrix • It gives you location of the vanishing point. • The homogeneous coordinate (x,y,0) is the ideal point or point at infinity in the direction of (x,y). (how??) (guess how to represent point at infinity in x direction), where will this appear in Image

  9. Camera Calibration • Why? To find how the object coordinated are projected in image plane • Parameters: Intrinsic & Extrinsic • Model

  10. contd.. From the figure, hence, In other words, => In some cases focal lengths can be different in x and y direction fu , fv f, uo,vo are intrinsic parameters

  11. Extrinsic Parameters • In general, the three dimensional world coordinates of a point will not be specfied in a frame whose origin is at the centre of projection • So we can transform by a linear transformation ( Rotation and Scale) Where T is 4x4 transformation matrix, R pure rotation (rigid body), t is the rigid body translation

  12. Types of Image Transformation (or Deformation)

  13. Color Models • Three independent quantities are used to describe any particular color. (HVS) • Achromatic light has no color - its only attribute is quantity or intensity. Greylevel is a measure of intensity. • On the other hand, brightness or luminance is determined by the perception of the color • Color depends primarily on the reflectance properties of an object.

  14. contd… • The tristimulus theory of color perception seems to imply that any color can be obtained from a mix of the three primaries, red, green and blue • Color models provide a standard way to specify a particular color and specifies a 3D coordinate system or subspace • Any color that can be specified using a model will correspond to a single point within the subspace it defines

  15. RGB Model

  16. CMY Model • RGB model asks what is added to black to get a particular color, the CMY (cyan-magenta-yellow) model asks what is subtracted from white. • Appropriate to absorption of colors, used in printing devices and filters

  17. HSI Model • The hue is determined by the dominant wavelength • The saturation is determined by the excitation purity, and depends on the amount of white light mixed with the hue • the intensity is determined by the actual amount of light

  18. YIQ • YIQ (luminance-inphase-quadrature) is Recoding of RGB for color television

  19. Some points to think about.. • what is the best way to apply the image processing techniques color images ? • Which color space to choose ? • If we want to increase the contrast in a dark image by histogram equalization, can we just equalize each color independently?

  20. Some quick facts • Normally Image is array of RGB values of pixels in BGR order • N-bit , m channel Image => It has m color spaces having N bit quantized data per color space per pixel (Ex. 8 bit RGB Image) • Very Simple data structure is Bitmap Format and Raw • JPEG widely used to store/capture images but it is compressed form

  21. Home Work • Install OpenCV (Intel Open Source Lib) http://sourceforge.net/projects/opencvlibrary • Check its documentation and see how image is described by IplImage data structure http://www.cs.bham.ac.uk/resources/courses/robotics/doc/opencvdocs/ • Try to write and run sample programs given in OpenCV tutorial and see for different images loss in JPEG format I will mail you.

  22. ThE eNd

More Related