Outline Announcement Texture modeling - continued Some remarks Applications of texture modeling

Visual Perception 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 11/19/2018 Visual Perception Modeling

Comments on General Feature Statistics 11/19/2018 Visual Perception Modeling

Visual Perception Modeling 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 over-constrained model will include only the original image 11/19/2018 Visual Perception Modeling

Multi-resolution Sampling 11/19/2018 Visual Perception Modeling

Multi-resolution Sampling – cont. 11/19/2018 Visual Perception Modeling

Multi-resolution Sampling – cont. More results at http://www.ai.mit.edu/~jsd 11/19/2018 Visual Perception Modeling

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 11/19/2018 Visual Perception Modeling

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 11/19/2018 Visual Perception Modeling

Applications of Texture Models – cont. 11/19/2018 Visual Perception Modeling

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 11/19/2018 Visual Perception Modeling

Applications of Texture Models – cont. Remote sensing Texture analysis has been used extensively to classify remotely sensed images Land use classification Automated image analysis 11/19/2018 Visual Perception Modeling

Applications of Texture Models – cont. 11/19/2018 Visual Perception Modeling

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 11/19/2018 Visual Perception Modeling

Applications of Texture Models – cont. 11/19/2018 Visual Perception Modeling

Content-based Image Retrieval Image retrieval example using spectral histogram 1st (Distance: 0.05) 6th (Distance: 0.14) 12th (Distance: 0.21) http://www-dbv.cs.uni-bonn.de/image/mixture.tar.gz 11/19/2018 Visual Perception Modeling

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 11/19/2018 Visual Perception Modeling

Texture Segmentation - continued Identify feature statistics using spatial constraints Pixels within a homogenous region have similar spectral histogram Input image Initial regions 11/19/2018 Visual Perception Modeling

Texture Segmentation - continued Classify each pixel using the extracted feature statistics Error with respect to the ground truth is 6.55 % Initial classification result Error from the ground truth 11/19/2018 Visual Perception Modeling

Texture Segmentation - continued Boundary localization using structural information The segmentation error is 0.95 % Segmentation result Error from the ground truth 11/19/2018 Visual Perception Modeling

Texture Segmentation - continued 11/19/2018 Visual Perception Modeling

Texture Segmentation - continued Input image Result superimposed Canny edge map Segmentation result 11/19/2018 Visual Perception Modeling