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CSE 8331 Spring 2010 Image Mining

CSE 8331 Spring 2010 Image Mining. Margaret H. Dunham Department of Computer Science and Engineering Southern Methodist University. The 2000 ozone hole over the antarctic seen by EPTOMS http://jwocky.gsfc.nasa.gov/multi/multi.html#hole. Table of Contents. Image Mining – What is it?

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CSE 8331 Spring 2010 Image Mining

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

  2. The 2000 ozone hole over the antarctic seen by EPTOMS http://jwocky.gsfc.nasa.gov/multi/multi.html#hole

  3. Table of Contents • Image Mining – What is it? • Feature Extraction • Shape Detection • Color Techniques • Video Mining • Facial Recognition • Bioinformatics

  4. Image Mining – What is it? • Image Retrieval • Image Classification • Image Clustering • Video Mining • Applications • Bioinformatics • Geology/Earth Science • Security • …

  5. Feature Extraction • Identify major components of image • Color • Texture • Shape • Spatial relationships • Feature Extraction Tutorial http://facweb.cs.depaul.edu/research/vc/VC_Workshop/presentations/pdf/daniela_tutorial2.pdf

  6. Shape Detection • Boundary/Edge Detection http://www.pages.drexel.edu/~weg22/can_tut.htmlSegmentation • Segmentation http://www.cs.toronto.edu/~jepson/csc2503/segmentation.pdf • Time Series – Eamonn Keogh http://www.engr.smu.edu/~mhd/8337sp07/shapes.ppt

  7. Color Techniques • Color Representations RGB: http://www.topbits.com/rgb.html HSV: http://www.topbits.com/hsv.html • Color Histogram • Color Anglogram http://www.cs.sunysb.edu/~rzhao/publications/VideoDB.pdf

  8. What is Similarity? (c) Eamonn Keogh, eamonn@cs.ucr.edu

  9. Video Mining • Boundaries between shots • Movement between frames • ANSES: http://mmir.doc.ic.ac.uk/demos/anses.html

  10. Facial Recognition • Based upon features in face • Convert face to a feature vector • Less invasive than other biometric techniques • http://www.face-rec.org • http://computer.howstuffworks.com/facial-recognition.htm • SIMS: http://www.casinoincidentreporting.com/Products.aspx

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

  12. Affymetrix GeneChip® Array http://www.affymetrix.com/corporate/outreach/lesson_plan/educator_resources.affx

  13. Microarray Data - Clustering "Gene expression profiling identifies clinically relevant subtypes of prostate cancer" Proc. Natl. Acad. Sci. USA, Vol. 101, Issue 3, 811-816, January 20, 2004

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