CSE 8331 Spring CSE 8331 Spring 2010 Image Mining Margaret H. Dunham Department of Computer Science and Engineering Southern Methodist University

2 CSE 8331 Spring 2010 The 2000 ozone hole over the antarctic seen by EPTOMS

3 CSE 8331 Spring 2010 Table of Contents Image Mining – What is it? Image Mining – What is it? Feature Extraction Feature Extraction Shape Detection Shape Detection Color Techniques Color Techniques Video Mining Video Mining Facial Recognition Facial Recognition Bioinformatics Bioinformatics

4 CSE 8331 Spring 2010 Image Mining – What is it? Image Retrieval Image Retrieval Image Classification Image Classification Image Clustering Image Clustering Video Mining Video Mining Applications Applications –Bioinformatics –Geology/Earth Science –Security –…

5 CSE 8331 Spring 2010 Feature Extraction Identify major components of image Identify major components of image Color Color Texture Texture Shape Shape Spatial relationships Spatial relationships Feature Extraction Tutorial Feature Extraction Tutorial op/presentations/pdf/daniela_tutorial2.pdf op/presentations/pdf/daniela_tutorial2.pdf

6 CSE 8331 Spring 2010 Shape Detection Boundary/Edge Detection Boundary/Edge Detection mlSegmentation mlSegmentation Segmentation Segmentation mentation.pdf mentation.pdf Time Series – Eamonn Keogh Time Series – Eamonn Keogh apes.ppt apes.ppt

7 CSE 8331 Spring 2010 Color Techniques Color Representations Color Representations RGB: HSV: Color Histogram Color Histogram Color Anglogram Color Anglogram DB.pdf DB.pdf

8 CSE 8331 Spring 2010 What is Similarity ? (c) Eamonn Keogh,

9 CSE 8331 Spring 2010 Video Mining Boundaries between shots Boundaries between shots Movement between frames Movement between frames ANSES: ANSES:

10 CSE 8331 Spring 2010 Facial Recognition Based upon features in face Based upon features in face Convert face to a feature vector Convert face to a feature vector Less invasive than other biometric techniques Less invasive than other biometric techniques recognition.htm recognition.htm recognition.htm recognition.htm SIMS: SIMS: aspx aspx

11 CSE 8331 Spring 2010 Microarray Data Analysis Each probe location associated with gene Each probe location associated with gene Measure the amount of mRNA Measure the amount of mRNA Color indicates degree of gene expression Color indicates degree of gene expression Compare different samples (normal/disease) Compare different samples (normal/disease) Track same sample over time Track same sample over time Questions Questions –Which genes are related to this disease? –Which genes behave in a similar manner? –What is the function of a gene? Clustering Clustering –Hierarchical –K-means

12 CSE 8331 Spring 2010 Affymetrix GeneChip ® Array

13 CSE 8331 Spring 2010 Microarray Data - Clustering "Gene expression profiling identifies clinically relevant subtypes of prostate cancer" Proc. Natl. Acad. Sci. USA, Vol. 101, Issue 3, , January 20, 2004