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Image Mosaics

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Pixel - a single point in an image. Representation. Red ... 'Jigsaw' Mosaic. Algorithm overview. For each region: Get average color value. Search Library ... – PowerPoint PPT presentation

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Title: Image Mosaics


1
Image Mosaics
  • by Kiril Stanoev

2
Outline
  • Image Processing Basics
  • What is image mosaics?
  • Types of mosaics
  • Algorithm overview
  • Development Process
  • Demonstration
  • References

3
Image Processing Basics
  • Pixel - a single point in an image
  • Representation
  • Red channel (0 255)
  • Green channel (0 255)
  • Blue channel (0 255)

4
Image Processing Basics
  • Average Color Value - Image

width 200 px
int redChannel, greenChannel, blueChannel For
each pixel in image redChannel
pixel.R greenChannel pixel.G blueChannel
pixel.B redChannel / totalPixels greenChann
el / totalPixels blueChannel / totalPixels
height 200 px
int totalPixels width height
avgColorValue redChannel, greenChannel,
blueChannel
5
Image Processing Basics
  • Average Color Value - Region

region width 20px region height 20px
6
What is Image Mosaics?
Process
Input Image
Output Image
7
Types of mosaics
ACV Mosaic
8
Types of mosaics
Grayscale Mosaic
9
Types of mosaics
Edge Detection Mosaic
10
Types of mosaics
Jigsaw Mosaic
11
Algorithm overview
Image Library
  • For each region
  • Get average color value
  • Search Library

image1
image2
image3
image4
...
Resize image
Replace region with image
12
Output
13
Recap
  • Image Processing Basics
  • What is image mosaics?
  • Types of mosaics
  • Algorithm overview
  • Development Process
  • Demonstration
  • References

14
Development process
  • Library Optimization
  • Color Correction Optimization
  • Refactoring

15
Library Optimization
  • Files ? Hashtable linear search

Hashtable
Key
Value
path to image
avg color value
path to image
avg color value
Linear search
path to image
avg color value
path to image
avg color value


16
Binary Search
  • Hashtable ? ArrayList of custom type binary
    search

Middle element of sorted array
17
Color Correction Optimization
  • Pixel by pixel ? Unsafe

18
Demonstration
  • Murphys Law
  • If anything can go wrong, it will!

19
References
  • Google.com
  • http//www.cs.princeton.edu/gfx/proj/mosaic/prince
    ton-cs-tr-574-98.pdf

20
Thank You for Your Attention
  • Questions?
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