This slides about Fundamental Steps of Digital Image Processing. This PPT is used for Academic Purpose Only.

1. Digital Image Processing
&
Pattern Recognition
Kalyan Acharjya
kalyan5.blogspot.in
Lecture 3
Unit 1: Second Part
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2. Levels of Image Understanding
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• Low Level-Involve primitive operations.
e.g. Image Preprocessing, noise reduction,
Enhancement etc.
Image input - Image Out
• Mid Level-
Image segmentation, identify particular objects.
Image input - Attributes extracted from those images
e.g. edges, contour, identify etc.
• High Level-Involving making sense of an ensemble of recognize objects, image
analysis and far end the functions normally associated with human vision.
Image
•Processing
Image
•Analysis
Image
•Measurements

3. Fundamental Steps of Digital Image
Processing
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4. Image Acquisition
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Image Enhancement

6. What is Image Restoration?
• Image restoration attempts to restore images that have been
degraded
 Identify the degradation process and attempt to reverse it.
 Almost Similar to image enhancement, but more objective.
Fig: Degraded image Fig: Restored image
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7. Color Issue of an Image
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• Red, Green and Blue Color cube
• Consider Each element=8 bit
• R,G,B ~0 to 255
• Grey scale f(x , y , L)
• 256 Grey shades
• Color Scale f(x , y, r , g , b)-24 bit
• 255x255x255=16777216 colors

8. RGB Components of an Image
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9. CMY and CMYK Color Model
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• Cyan(C), Magenta(M) and Yellow(Y) are the secondary colors of light.
• Or CMY are Primary colors of pigments.
• RGB to CMY
• Black=Cyan + Magenta + Yellow
• Printing Industry used to four color Printing.
• Cyan, Magenta, Yellow plus Black.
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B
G
R
Y
M
C
1
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10. HIS Color Model
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• RGB to HSI Conversion
1,,,0where),(
3
1
 BGRIBGRI
002
1
if},
))(()(
)]()[(
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{cos bg
BGBRGR
BRGR
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00if,360 bgHH  
}),,(min{
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BGR
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IBbIGg /,/where 00 
-Hue : Range [0, 360]
-Saturation : Range[0, 1]
-Intensity : Range[0, 1]

11. Image Compression?
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• How we stored the image: Reduce the size for storage .
• How analog image world is relate to digital processing world.
• Compression-Remove redundancies.
• Transmission with minimum bandwidth.
• Lossy Compression=redundancy +some information, but still acceptable.
Original Image
Size-116 KB
Compressed Image
Size-12.9 KB, 11 %
Compressed Image
Size-1.95 KB, 1.6 %

12. Morphological Image Processing
Extract image components that are useful in the representation and
description of region shape, such as-
•Boundaries extraction
•Skeletons
•Convex hull
•Morphological filtering
•Thinning
•Pruning…many More
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13. Image Segmentation
In computer vision, Image Segmentation is
the process of partitioning a digital
image into multiple segments. The goal of
segmentation is to simplify and/or change
the representation of an image into
something that is more meaningful and
easier to analyze
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14. Image Representation & Description
• Image representation & description: After an image is
segmented into regions; the resulting aggregate of segmented
pixels is represented & described for further computer
processing.
• Representation and Description
– Representing regions in 2 ways:
– Based on their external characteristics (its boundary):
– Shape characteristics
• Based on their internal characteristics (its region):
– Regional properties: color, texture, and …
• Both
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15. Image Representation
&
Description
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16. Object Recognition
Object Detection is the process of finding instances of objects in
images. .This allows for multiple objects to be identified and located
within the same image.
 Object recognition can be termed as identifying a specific object
in a digital image or video. Object recognition have immense of
applications in the field of monitoring and surveillance, medical
analysis, robot localization and navigation etc.
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17. Components of Image Processing System
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18. Popular Image Processing Software
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• CVIP tools
(Computer Vision and Image Processing tools)
• Intel Open Computer Vision Library
• Microsoft Vision SDL Library
• MATLAB
• KHOROS
• ImageJ

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Applications of
Digital Image Processing?

20. Applications of Digital Image Processing
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• Identification.
• Robot vision.
• Steganography.
• Image Enhancement.
• Image Analysis in Medical.
• Morphological Image Analysis.
• Space Image Analysis.
• IC Industry……….etc.

21. Let’s Review : Unit 1
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Image
Different Imaging Modalities
Steps in Digital Image Processing
Steps in Digital Image processing

22. Year 2018: Still Imaging Challenge? Future
• Airport Security (Indian Airlines Hijack)
• 9/11 Incident
• Tumor detection in 1st stage ….
• Many more…
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23. Thank You
for
Your Attention
This PPT is available at kalyan5.blogspot.in
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Contact E-mail: kalyan.acharjya@gmail.com