1. Digital Image Processing In The Name Of God Digital Image Processing Lecture1: Introduction M. Ghelich Oghli By: M. Ghelich Oghli E-mail: m.g31_mesu@yahoo.com Fall 2012 tvtoitc.ir

2. 1. Digital Image Processing, Third Edition (Text Book) Rafael C. Gonzalez and Richard E. Woods 2. Digital Image Processing Using MATLAB Rafael C. Gonzalez and Richard E. Woods References

3. 3. Digital Image Processing, 5 th Edition Bernd Jahne 4. Digital Image Processing, Third Edition WILLIAM K. PRATT 5. Handbook of Image and Video Processing AL Bovik References

4. What is Image Processing Image processing is a subclass of signal processing concerned specifically with pictures. Improve image quality for human perception and/or computer interpretation.

5. Why Image Processing? The future is multimedia information processing Images and videos are everywhere Many and diverse application –Astronomy, Biology, Geology, Geography, Medicine, Law enforcement, Defense, Industrial inspection, … –Different imaging modalities: Visual, X-Ray, Ultrasound, Infra-red, ….

6. Digital Image Processing and Analysis

7. Image Analysis Image Analysis and Computer Vision Image Analysis involves examination of image data to facilitate solving an imaging problem In a Image analysis system outputs are used by human A Computer Vision application can be considered to be a deployed image analysis system In a Computer Vision system the images are intended to be “use” by a computer These two categories overlap each other in certain areas. Computer Vision

8. Some Applications of DIP and Computer Vision Image Enhancement Military applications: target tracking,… Security and Biometrics: face detection, Gesture recognition finger print,… Electronics Medical Image Analysis Industrial automation: QC, barcode reading, defect detection, label checking,… Scene interpretation Law Enforcement Geographical Information System (GIS) Robotics …

9. Some Applications of DIP and Computer Vision Image Enhancement One of the most common uses of DIP techniques: improve quality, remove noise etc

10. Some Applications of DIP and Computer Vision Security and Biometrics face detection finger print Gesture recognition

11. Fingerprint Identification System IBM fingerprint laptop Hanwang fingerprint attendance machine Lock Some Applications of DIP and Computer Vision

12. Fingerprint Identification System Some Applications of DIP and Computer Vision Doo-shaped pattern Bow-shaped pattern Loop

13. Fingerprint Identification System diagram Some Applications of DIP and Computer Vision

14. Electronics: PCB –Machine inspection is used to determine that all components are present and that all solder joints are acceptable –Both real imaging and x-ray imaging

15. Some Applications of DIP and Computer Vision Medical Image Analysis –Extraction clinically useful information for Diagnosis –Various types of medical images Radiography Skull Radiography Mammography

16. Medical Image Analysis –Various types of medical images Infrared thermography Some Applications of DIP and Computer Vision Flow Analysis

17. Medical Image Analysis –Various types of medical images Some Applications of DIP and Computer Vision Brain MRI Ultrasound PET Angiography

18. Medical Image Analysis –Various types of medical images Some Applications of DIP and Computer Vision FMRI

19. Medical Image Analysis –Various types of medical images Cardiac MRICardiac CT Some Applications of DIP and Computer Vision

20. Medical Image Analysis –Various types of medical images Some Applications of DIP and Computer Vision

21. Industrial Inspection  Human operators are expensive, slow and unreliable  Make machines do the job instead  Industrial vision systems are used in all kinds of industries  Can we trust them? Some Applications of DIP and Computer Vision

22. Scene interpretation

23. Law Enforcement Image processing techniques are used extensively by law enforcers –Number plate recognition for speed cameras/automated toll systems Some Applications of DIP and Computer Vision

24. Geographical Information System (GIS) Digital image processing techniques are used extensively to manipulate satellite imagery Why GIS ?  To inventory and monitor resources  To test the sensitivity of our analysis assumptions  To simulate potential impacts of management alternatives Some Applications of DIP and Computer Vision

25. Geographical Information System (GIS) Some Applications of DIP and Computer Vision The photo shows a great deal of the Yangtze River sediment Remote monitoring of forest conditions (green for the forest)

26. Geographical Information System (GIS) Some Applications of DIP and Computer Vision Taklimakan desert Remote sensing image

27. Robotics Some Applications of DIP and Computer Vision

28. Image/ Video Processing Methods Image Enhancement Image Restoration Compression Image Reconstruction Morphological Image Processing Image Segmentation Feature Extraction and Recognition Computer Vision

29. Image Enhancement Techniques concern the improvement of the quality of the digital image Original Image Enhanced image

30. Image Restoration Improving the appearance of an image Tend to be based on mathematical or probabilistic models of image degradation Distorted image Restored image Geometric distorted image Restored image

31. Image Compression Reducing the storage the storage required to save an image

32. Morphological Processing Tools for extracting image components that are useful in the representation and description of shape.

33. Segmentation To partition the image into its constituent parts (objects) –Autonomous segmentation (very difficult) Can facilitate or disturb subsequent processes –Output (representation): Raw pixel data, depicting either boundaries or whole regions (corners vs. texture for example) Need conversion to a form suitable for computer processing –(Description)

34. Representation & Description Feature selection (description) deals with extracting: –features that result in quantitative information of interest or –features that are important for differentiating one class of objects from another

35. Recognition & Interpretation To assign a label to an object based on information provided by the descriptors To assign meaning to a group of recognized objects