geometric activity indices for classification of urban man-made objects using very-high resolution...
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Geometric Activity Indices for Classification
of Urban man-made Objects using Very-High Resolution Imagery
R. Bellens, L. Martinez-Fonte, S. Gautama
Ghent University, Belgium
Geometric Activity IndicesIntroduction
2/23
Experimental Results
Outline
1. Introduction• Use of Spatial Information for Land-Use Classification• Per Pixel Geometric Activity Indices
– Evaluation
2. Geometric Activity Indices• Raw indices
– Ridge-based– Morphological
• Summarized Indices• Object-based Indices for Evaluation
3. Experimental results• Settings and Classes Definition• Results and Discussion
Geometric Activity IndicesIntroduction
3/23
Experimental Results
Outline
1. Introduction• Use of Spatial Information for Land-Use Classification• Per Pixel Geometric Activity Indices
– Evaluation
2. Geometric Activity Indices• Raw indices
– Ridge-based– Morphological
• Summarized Indices• Object-based Indices for Evaluation
3. Experimental results• Settings and Classes Definition• Results and Discussion
Introduction
Geometric Activity IndicesIntroduction
4/23
Experimental Results
Use of Spatial Information for Land-Use Classification
Classification
Introduction
Geometric Activity IndicesIntroduction
5/23
Experimental Results
Use of Spatial Information for Land-Use Classification
Classification
Introduction
• Morphological profile (Benediktsson)
•Shape Descriptors from Angular Texture
Signature (Couloigner)
•Edge Maps (Haverkamp)
•Corner Points and Edges (Phalke &
Couloigner)
Geometric Activity IndicesIntroduction
6/23
Experimental Results
Classification
Introduction
Per Pixel Classification
1. Detection of image features (e.g. lines)
2. Generate per-pixel activity indices (e.g.
indication of the presence of a line)
3. Each index is an input layer to the
classification, together with
spectral bands.
Hipotesis: Man-made objects usually exhibit nice geometric features, then Geometric Activity can indicate a specific type of man-made object.
Geometric Activity IndicesIntroduction
7/23
Experimental Results
Geometric Activity+
Spectral bands
Introduction
Per Pixel Classification - Evaluation
Object-based features (e-cognition)
+ Spectral bands
Classification
Geometric Activity IndicesIntroduction
8/23
Experimental Results
Outline
1. Introduction• Use of Spatial Information for Land-Use Classification• Per Pixel Geometric Activity Indices
– Evaluation
2. Geometric Activity Indices• Raw indices
– Ridge-based– Morphological
• Summarized Indices• Object-based Indices for Evaluation
3. Experimental results• Settings and Classes Definition• Results and Discussion
Geometric Activity Indices
Geometric Activity IndicesIntroduction
9/23
Experimental Results
Geometric Activity Indices
1. Raw indices scale-space signatures each scale = 1 image layer
– Ridge-based
– Morphological
2. Summarized Indices
3. Object-based Indices for Evaluation
Geometric Activity Indices
scale
Index value
Per-pixel signature
1 3 5 7 9 11 13
99
0
099
9999
99
scale 1scale 3
scale 5scale 7
scale 9
…
Geometric Activity IndicesIntroduction
10/23
Experimental Results
Raw Ridge-based Indices
Gradient and Eigenvalues of the Hessian matrix
(Steger98)
2 4 5
3 5 6
2 2
24 5
2 25 6
2
2( ) ,
2
2( )
2
Ta a i a jI I
gradient Ia a i a jx y
I Ia ax x y
Hessian Ia aI I
y x y
||G|| 1 2 class
0 0 0 flat
0 - - peak
0 + + valley
0 - 0 ridge
0 + 0 valley
+ 0 0 slope
+ - - slope
+ + + slope
Geometric Activity Indices
Geometric Activity IndicesIntroduction
11/23
Experimental Results
Raw Ridge-based IndicesGeometric Activity Indices
Original image
Gradient MinEigenvalue
Window size = 11
MaxEigenvalue
Geometric Activity IndicesIntroduction
12/23
Experimental Results
Raw Morphology-based Indices
Closing with Disk
0 4 8 12
Geometric Activity Indices
Open/Closing with circular structuring elementOpen/Closing with linear structuring element
Geometric Activity IndicesIntroduction
13/23
Experimental Results
Raw Morphology-based Indices
Closing with Lines
0 8 16 24
Geometric Activity Indices
Open/Closing with circular structuring elementOpen/Closing with linear structuring element
Geometric Activity IndicesIntroduction
14/23
Experimental Results
Summarized Indices
Software tool interface for the Multiple Discriminant Analysis and generation of summary geometry activities features
Geometric Activity Indices
Multiple Discriminant Analysis (MDA)
Geometric Activity IndicesIntroduction
15/23
Experimental Results
# of features Based on
4 Maxeigen, Mineigen and Gradient signatures
4 Closing signatures with disk
2 Opening signatures with disk
3 Open/Close with linear structuring elements
Summarized IndicesGeometric Activity Indices
Sample feature 2
Indication of small dark structures
(based on Closings)
Sample feature 1
Indication of large roads
(based on Ridge)
Geometric Activity IndicesIntroduction
16/23
Experimental Results
Object-based Indices used for Evaluation (6/24)Geometric Activity Indices
(Calculated with e-cognition)
Geometric Activity IndicesIntroduction
17/23
Experimental Results
Outline
1. Introduction• Use of Spatial Information for Land-Use Classification• Per Pixel Geometric Activity Indices
– Evaluation
2. Geometric Activity Indices• Raw indices
– Ridge-based– Morphological
• Summarized Indices• Object-based Indices for Evaluation
3. Experimental results• Settings and Classes Definition• Results and Discussion
Experimental Results
Geometric Activity IndicesIntroduction
18/23
Experimental Results
Experimental Results
QuickBird
panchromatic: 60 cm multispectral: 2.4 m
bluegreenredinfra-red
Experimental Results
Geometric Activity IndicesIntroduction
19/23
Experimental Results
Classes DefinitionExperimental Results
Geometric Activity IndicesIntroduction
20/23
Experimental Results
Classification Scenarios
Only Spectral information (4xs + pan) and NDVI
6 layers
Geometric Activities (GA) indices
+13 features
Object-based features (eCognition®)
+24 features
Combined GA and Object-based indices
+37 features
Experimental Results
Geometric Activity IndicesIntroduction
21/23
Experimental Results
Effect of Adding Geometric Activity IndicesExperimental Results
Spectral features
only
Spectral +
GA features
Geometric Activity IndicesIntroduction
22/23
Experimental Results
Geometric Activity vs Object-based IndicesExperimental Results
Spectral +
GA features
Spectral +
Object-basedfeatures
Geometric Activity IndicesIntroduction
23/23
Experimental Results
Man-Made Objects Classification AccuracyExperimental Results
Geometric Activity IndicesIntroduction
24/23
Experimental Results
Conclusions (1 / 2)
Ridge features:• Per-pixel indication of the presence of a linear structure• Problem: unreliability near borders (good to locate roads, not
for delineation of roads)• little improvement in distinguishing between the road class
and the roof class• Improves distinction of the classes water and shadow
(geometrically these classes are very different: the class water consists of mainly large objects, which results in very low responses on the lower scales, while the class shadow consists of small objects, which results in high responses on the lower scales) Since the water objects are very large, only a small part of
it is affected by border effects
Geometric Activity IndicesIntroduction
25/23
Experimental Results
Conclusions (2 / 2)
Morphological features• Disk shaped structuring elements
• indication of the minimum size of objects• Derived features seemed especially useful for
detecting isolated houses• Linear structuring elements
• indication of the maximum size of objects • Useful to detect linear objects which have large
maximum and small minimum sizes• Together, these features gave significant improvements
on the accuracies of the class roof and especially of the class road.
Geometric Activity Indices for Classification
of Urban man-made Objects using Very-High Resolution Imagery
R. Bellens, L. Martinez-Fonte, S. Gautama
Ghent University, Belgium