chapter 6 color shading
Download
Skip this Video
Download Presentation
Chapter 6. Color & Shading

Loading in 2 Seconds...

play fullscreen
1 / 26

Chapter 6. Color & Shading - PowerPoint PPT Presentation


  • 118 Views
  • Uploaded on

Chapter 6. Color & Shading. Perception of objects. Perception of objects. The spectrum (energy) of light source . The spectral reflectance of the object surface . The spectral sensitivity of the sensor. How do we see an object?. Light. Eyes. Object. Luminance  Lightness

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' Chapter 6. Color & Shading' - long


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.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
perception of objects1
Perception of objects
  • The spectrum (energy) of light source.
  • The spectral reflectance of the object surface.
  • The spectral sensitivity of the sensor.
how do we see an object
How do we see an object?

Light

Eyes

Object

  • Luminance  Lightness
  • Chrominance  Color

Human eye is more sensitive to luminance than to chrominance

rgb colors
RGB Colors
  • Colors specify:
    • A mixture of red, green, and blue light
    • Values between 0.0 (none) and 1.0 (lots)
  • Color
  • Red Green Blue
  • White 1.0 1.0 1.0
  • Black 0.0 0.0 0.0
  • Yellow 1.0 1.0 0.0
  • Magenta 1.0 0.0 1.0
  • Cyan 1.0 1.0 0.0
yiq model
YIQ Model
  • TV transmission  digital space  YCBCR
  •  analog space  YIQ (NTSC)
  •  YUV (PAL)
color histogram
Color Histogram
  • Color Histogram are relatively invariant to
    • Translation
    • Rotation
    • Scaling
  • Simple methods for color histogram construction
    • Concatenate the higher order two bits of each RGB color code.  64 bins
    • Compute three separate RGB histograms (4 bits each) and just concatenate them into one.  48 bins
similarity measure for histogram matching
Similarity measure for histogram matching
  • It is common to smoothing the histogram before matching
  •  to adapt minor shifts of the reflectance spectrum.
color segmentation
Color Segmentation

A plot of pixels (r,g) taken from different images containing faces.

(r,g) : normalized red and green values

face detection
Face Detection
  • Face region classification. (R>G>B)
  • Connected Component Labeling.
  • Select the largest component as face object assuming there is only one face in the image.
  • Discard remaining components or merges them with the face object.
  • Computing the location of eyes and nose.
three types of material reflection
Three types of Material Reflection
  • Diffuse Color of reflected light from diffuse reflection (light scattered randomly)
  • Ambient Amount of background light the surface reflects
  • Specular Color of reflected light from specular reflection (light reflected in a regular manner)
complications
Complications
  • The above models of illumination and reflection are simplified.
  • Some objects reflect light as well as emit light. For example: light bulbs.
  • In uncontrolled scenes, such as outdoor scenes, it is much more difficult to account for the different phenomena.
ad