automatic image orientation detection
Post on 06-Jan-2016
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DESCRIPTION
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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 imagesDefine criteria for images to separate
them to 4 groups: Efficiency: DB size, vector size, runtime.
What is Color?
What is Color?
Color representation - RGB
Color difference - RGB
Color representation - HSV
Classify function in MatLab
Peripheral blocks
Edge ratio
Feature VectorImage resolution = 800X600NXN blocks4N-4 peripheral blocksFor each block:
◦Mean of H,S,V◦Var of H,S,V◦Edge density
Vector size: N=4
Block size : 16peripheral blocks: 12
Vector size:12*(3+3+1)+4 = 88
Results% Test
sizeVector
sizeFeature Vector
Color scheme
DB size
N
62% 50 24 Mean RGB 200 3
%34 50 48 Mean+var RGB 200 3
76% 70 24 Mean HSV 300 4
79% 400 37 Mean+edge HSV 300 4
82% 400 88 Mean+Var+edge
HSV 300 4
81% 200 200Mean+Var+edg
eHSV 300 8
Results
Results
Future workImproving the feature vectorTesting new method of “machine
learning” Add a rejection criteriaAdd classifier of indoor/outdoorAdd an object recognition
algorithm
Thank you !
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