This presentation covers digital image processing, explaining its definition, history, and various applications including noise filtering, remote sensing, and industrial inspection. Key topics discussed include the importance of pixels, the evolution of imaging technology, and examples such as the Hubble Telescope and its image processing corrections. The document emphasizes the relevance of digital image processing in fields like medicine, law enforcement, and human-computer interaction.

1. Welcome to our
Presentation
Presentation Topic: Digital Image Processing

2. Group Members
Mohammad Salim Hosen (162-15-1044)
Md. Rifat Rahman (162-15-1049)
Arifur Jaman (153-15-607)
Shahedul Islam Rishad (162-15-1029)
Team: Dream Crushers

3. CONTENTS:
 What is Digital Image?
 What is digital image processing?
 Pixel
 Applications
 Examples of digital image processing

4. Digital Image:
 A digital image is a representation of a two-dimensional image as a finite set of
digital values, called picture elements or pixels.

5. Digital Image Processing:
Digital image processing focuses on two major tasks:
 Improvement of pictorial information for human interpretation.
 Processing of image data for storage, transmission and representation for
autonomous machine perception.

6. Pixel:
 It is the smallest controllable element
of an image.
 More pixels then more clearer the
image
 Pixels have different intensity values

7. History
 In 1920s Submarine cables were used to transmit digitized newspaper
pictures between London and New York using Bartlane systems.
 Specialized printing equipments were used to code the images and
reproduced at receiver using telegraphic printers.
Fig. Image produced using telegraphic printer

8. History
In 1921, photographic printing press improved the resolution and tonal
quality of images.
Bartlane system was capable of coding 5 distinct brightness levels.
It increased to 15 by 1929

9. History
 After 35 years of improvement in processing technique
In 1964, Computer processing techniques were used to improve picture of
moon transmitted by Ranger 7 at JPL.
This was the basis of modern image processing technique.

10. The continuum from image processing to computer vision can
be broken up into low, mid and high-level processes:

11. Block Diagram of a Typical
Image Processing Sequence:

12. Components of Image Processing System

13. Applications:
 Noise filtering
 Content Enhancement
 Remote sensing

14. Filtering:

15. Image Enhancement:
 Contrast enhancement
 Deblurring

16. Image Deblurring:

17. Remote Sensing:

18. Remote Sensing:

19. Examples of digital image processing:
 IMAGE ENHANCEMENT: One of the most common uses of DIP
techniques: improve quality, remove noise etc

20. THE HUBBLE TELESCOPE:
 Launched in 1990 the Hubble telescope can take images of very distant objects However,
an incorrect mirror made many of Hubble’s images useless Image processing techniques
were used to fix this.

21. ARTISTIC EFFECTS:
 Artistic effects are used to make
images more visually appealing,
to add special effects and to
make composite images.

22. MEDICINE:
Take slice from MRI scan of canine heart, and find boundaries between types
of tissue:
 Image with gray levels representing tissue density
 Use a suitable filter to highlight edges

23. GIS:
Geographic Information Systems:
 Digital image processing techniques are used extensively to manipulate satellite
imagery
 Terrain classification
 Meteorology

24. 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

25. PCB INSPECTION:
Printed Circuit Board (PCB) inspection
 Machine inspection is used to determine that all components are present and that
all solder joints are acceptable.
 Both conventional imaging and x-ray imaging are used.

26. LAW ENFORCEMENT:
 Number plate recognition for speed cameras/automated toll systems
 Fingerprint recognition
 Enhancement of CCTV images

27. HCI: Try to make human computer interfaces more natural
 Face recognition
 Gesture recognition

28. THANK YOU