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AUTOMATIC IMAGE ORIENTATION DETECTION

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AUTOMATIC IMAGE ORIENTATION DETECTION - PowerPoint PPT Presentation


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AUTOMATIC IMAGE ORIENTATION DETECTION. Goal. Main Goal: For any given picture detect its orientation. Sub Goals: How to deal with color images Define criteria for images to separate them to 4 groups: Efficiency: DB size, vector size, runtime. What is Color?. What is Color?.

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Presentation Transcript
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Goal

Main Goal:

  • For any given picture detect its orientation.

Sub Goals:

  • How to deal with color images
  • Define criteria for images to separate them to 4 groups:
  • Efficiency: DB size, vector size, runtime.
feature vector
Feature Vector

Vector size: N=4

  • Image resolution = 800X600
  • NXN blocks
  • 4N-4 peripheral blocks
  • For each block:
    • Mean of H,S,V
    • Var of H,S,V
    • Edge density

Block size : 16

peripheral blocks: 12

Vector size:

12*(3+3+1)+4 = 88

future work
Future work
  • Improving the feature vector
  • Testing new method of “machine learning”
  • Add a rejection criteria
  • Add classifier of indoor/outdoor
  • Add an object recognition algorithm
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