CSE 53317331 Fall 2007 Image Mining Margaret H
- Slides: 13
CSE 5331/7331 Fall 2007 Image Mining Margaret H. Dunham Department of Computer Science and Engineering Southern Methodist University CSE 5331/7331 F'07 1
The 2000 ozone hole over the antarctic seen by EPTOMS CSE 5331/7331 F'07 http: //jwocky. gsfc. nasa. gov/multi. html#hole 2
Table of Contents Image Mining – What is it? n Feature Extraction n Shape Detection n Color Techniques n Video Mining n Facial Recognition n Bioinformatics n CSE 5331/7331 F'07 3
Image Mining – What is it? Image Retrieval n Image Classification n Image Clustering n Video Mining n Applications n – Bioinformatics – Geology/Earth Science – Security –… CSE 5331/7331 F'07 4
Feature Extraction n n n Identify major components of image Color Texture Shape Spatial relationships Feature Extraction & Image Processing http: //users. ecs. soton. ac. uk/msn/book/ n Feature Extraction Tutorial http: //facweb. cs. depaul. edu/research/vc/VC_Worksh op/presentations/pdf/daniela_tutorial 2. pdf CSE 5331/7331 F'07 5
Shape Detection n Blob http: //elib. cs. berkeley. edu/blobworld/ Boundary/Edge Detection n Time Series – Eamonn Keogh n http: //www. engr. smu. edu/~mhd/8337 sp 07/sh apes. ppt CSE 5331/7331 F'07 6
Color Techniques n n n Color Representations RGB: http: //en. wikipedia. org/wiki/Rgb HSV: http: //en. wikipedia. org/wiki/HSV_color_space Color Histogram Color Anglogram http: //www. cs. sunysb. edu/~rzhao/publications/Video DB. pdf CSE 5331/7331 F'07 7
What is Similarity? CSE 5331/7331 F'07 (c) Eamonn Keogh, eamonn@cs. ucr. edu 8
Video Mining Boundaries between shots n Movement between frames n ANSES: http: //mmir. doc. ic. ac. uk/demos/anses. html n CSE 5331/7331 F'07 9
Facial Recognition Based upon features in face n Convert face to a feature vector n Less invasive than other biometric techniques n http: //www. face-rec. org n http: //computer. howstuffworks. com/facialrecognition. htm n SIMS: n http: //www. casinoincidentreporting. com/Products. aspx CSE 5331/7331 F'07 10
Microarray Data Analysis n n n Each probe location associated with gene Measure the amount of m. RNA 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? n Clustering – Hierarchical – K-means CSE 5331/7331 F'07 11
® Gene. Chip Affymetrix Array http: //www. affymetrix. com/corporate/outreach/lesson_plan/educator_resources. affx CSE 5331/7331 F'07 12
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 CSE 5331/7331 F'07 13
- Strip mining vs open pit mining
- Strip mining before and after
- Difference between strip mining and open pit mining
- Web text mining
- Mining multimedia databases in data mining
- Mining complex types of data
- Cse 572 data mining
- Cse 572
- Real vs virtual image
- Real vs virtual image
- Translate
- Linear position invariant degradation
- Arithmetic coding in digital image processing
- Image segmentation in digital image processing