Outline
• Announcement
• Texture modeling - continued
– Some remarks
– Applications of texture modeling
Announcement
• The presentation schedule is on the web
– Now you should have almost completed your project
– You need to take it very seriously in order to get a good
grade for this class
5/29/2016
Visual Perception Modeling
2
Comments on General Feature Statistics
5/29/2016
Visual Perception Modeling
3
Joint Statistics
• FRAME and Julesz ensemble models use
marginal distributions of feature statistics
• It might be useful to consider joint statistics
for more powerful models
– Joint statistics will be more precise because filter
responses are not independent of each other
– However, this model should include all the
images of the same texture type; an overconstrained model will include only the original
image
5/29/2016
Visual Perception Modeling
4
Multi-resolution Sampling
5/29/2016
Visual Perception Modeling
5
Multi-resolution Sampling – cont.
5/29/2016
Visual Perception Modeling
6
Multi-resolution Sampling – cont.
More results at http://www.ai.mit.edu/~jsd
5/29/2016
Visual Perception Modeling
7
Applications of Texture Models
• Inspection
– There has been a limited number of texture
processing for automated inspection problems
– Detection of defects of textiles
– Detection of defects of lumber wood
automatically
5/29/2016
Visual Perception Modeling
8
Applications of Texture Models – cont.
• Medical image analysis
– Image analysis techniques have played an
important role in several medical applications
– Texture features are used to distinguish normal
tissues from abnormal tissues
5/29/2016
Visual Perception Modeling
9
Applications of Texture Models – cont.
5/29/2016
Visual Perception Modeling
10
Applications of Texture Models – cont.
• Document processing
– Document image analysis and character
recognition
• Applications ranging from postal address recognition
to interpretation of maps
– Based on the characteristics of printed documents
5/29/2016
Visual Perception Modeling
11
Applications of Texture Models – cont.
• Remote sensing
– Texture analysis has been used extensively to
classify remotely sensed images
• Land use classification
• Automated image analysis
5/29/2016
Visual Perception Modeling
12
Applications of Texture Models – cont.
5/29/2016
Visual Perception Modeling
13
Applications of Texture Models – cont.
• Content-based image retrieval
– Try to retrieve images that are meaningful in
certain sense
• For example, to find all the images that like the
examples
• To find all the images that contain a horse
5/29/2016
Visual Perception Modeling
14
Applications of Texture Models – cont.
5/29/2016
Visual Perception Modeling
15
Content-based Image Retrieval
• Image retrieval example using spectral histogram
http://www-dbv.cs.uni-bonn.de/image/mixture.tar.gz
1st (Distance: 0.05)
5/29/2016
6th (Distance: 0.14)
Visual Perception Modeling
12th (Distance: 0.21)
16
Applications of Texture Models – cont.
• Texture segmentation
– Image segmentation is to partition an image into
roughly homogenous regions
– Segmentation is more difficult than classification
• Feature statistics not known
• Boundaries to be localized
5/29/2016
Visual Perception Modeling
17
Texture Segmentation - continued
• Identify feature statistics using spatial constraints
– Pixels within a homogenous region have similar
spectral histogram
5/29/2016
Input image
Visual Perception Modeling
Initial regions
18
Texture Segmentation - continued
• Classify each pixel using the extracted feature statistics
Initial classification result
Error from the ground truth
– Error with respect to the ground truth is 6.55 %
5/29/2016
Visual Perception Modeling
19
Texture Segmentation - continued
• Boundary localization using structural information
Segmentation result
Error from the ground truth
– The segmentation error is 0.95 %
5/29/2016
Visual Perception Modeling
20
Texture Segmentation - continued
5/29/2016
Visual Perception Modeling
21
Texture Segmentation - continued
5/29/2016
Input image
Result superimposed
Canny edge map
Segmentation result
Visual Perception Modeling
22