Digital images are composed of a grid of pixels that are sampled from scenes or documents. A pixel is the smallest unit of an image and images can be grayscale, containing only black and white pixels, or RGB color images with red, green and blue subpixels. Digital image processing uses computer algorithms to modify images, such as smoothing or compressing them, in order to enhance the image or extract useful information. Some applications of image processing discussed are smoothing images using averaging filters of different sizes, compressing images using delta encoding by representing similar pixel values with delta values rather than individual values, and face detection using the Viola-Jones algorithm which uses Haar features, integral images, AdaBoost training, and cascading classifiers to rapidly detect

1. Digital IMAGE PROCESSING
Amir Hossain
13-23814-1

2. What is a image???

3. What is a Digital Image???

4. Digital Image
DIGITAL IMAGES are electronic snapshots taken
of a scene or scanned from documents, such as
photographs, manuscripts, printed texts, and
artwork. The digital image is sampled and
mapped as a grid of dots or picture elements
(pixels).

5. Our vs Computer vison

6. Let’s go to the image root(Continue)
pixel
• A pixel (abbr. for picture element) is the smallest unit of
an image.

7. Let’s go to the image root(Continue)
• MATLAB (Matrix Laboratory) stores images as
matrices.
• In MATLAB, image pixels are referenced using (row,
col) values.
• Origin of the coordinate system (1,1) is the top left
corner of the image

8. Let’s go to the image root
0.204.102 00000000 11001100 1100110
Image are two kinds:
• Grayscale/Black-white image(16 bit image)
Such as 11001100 1100110
Black white
• RGB/Color image(24 bit image)
Such as 00000000 11001100 1100110
Red(R) Green(G) Blue(B)
• Therefore, a 640x480 image is a matrix of 640 columns and 480
rows, each element of this matrix is called an image pixel.

9. In a summary
• Digital Image is nothing but collection of pixels
which are arrange in matrix form
• Pixel is consists of sub pixels(black and white
sub pixels for grayscale and red, blue and
green sub pixels for color image)
• This sub pixels have value which represented
in 8 bits binary number

10. What is Digital Image processing?
• Digital image processing is the is a method to
convert an digital Image in order to get an
enhanced image or to extract some useful
information from it by using
computer algorithms

11. Some Applications of image
processing

12. Smoothing Image(Gaussian blur
method)
1/9
1/9
1/9
1/9
1/9
1/9
1/9
1/9
1/9
Origin x
y Image f (x, y)
e = 1/9*106 +
Filter
1/9*104 + 1/9*100 + 1/9*108 +
1/9*99 + 1/9*98 +
1/9*95 + 1/9*90 + 1/9*85
= 98.3333
Simple 3*3
Neighbourhood
106
104
99
95
100 108
98
90 85
1/9
1/9
1/9
1/9
1/9
1/9
1/9
1/9
1/9
3*3 Smoothing
Filter
104 100 108
99 106 98
95 90 85
Original Image
Pixels
*
The above is repeated for every pixel in the
original image to generate the smoothed image

13. Image Smoothing Example
Images taken from Gonzalez & Woods, Digital Image Processing (2002)
Normal Image

14. Image Smoothing Example
Images taken from Gonzalez & Woods, Digital Image Processing (2002)
Using 3*3 filter

15. Image Smoothing Example
Images taken from Gonzalez & Woods, Digital Image Processing (2002)
Using 5*5 filter

16. Image Smoothing Example
Images taken from Gonzalez & Woods, Digital Image Processing (2002)
Using 9*9 filter

17. Image Compression(Delta Encoding)
Process of delta encoding
• Instate of every pixel value we consider group of
pixels where nearby pixels are most similar
• We give value according to similarity which
called delta value
• If neighbor pixels are identical then delta value=0

18. Image Compression(Delta Encoding)
Continue
• If almost identical then close to 0
• In a high regulation image neighbor pixels are a
lot more identical so the delta value looks like
this
• If we consider this
• We can express the group of pixel like this
• Png image follow this Encoding which is
lossless compression

19. Viola Jones face detection

20. Step 1:Haar feature(collect raw face
identifier)

21. Step 2: Integral Image (specific value
for identifier)

22. Integral Image(continue)

23. Step 3:Adaboost(find necessary
information)

24. Step 4:Cascading(detect face by
matching information)

25. Summary

26. Detected Image using Viola Jones

27. Thank You
Any Questions
???