Two-week ISTE workshop on Effective teaching/learning of computer programming

1
Two-week ISTE workshop onEffective
teaching/learning of computer programming

• Dr Deepak B Phatak
• Subrao Nilekani Chair Professor
• Department of CSE, Kanwal Rekhi Building
• IIT Bombay
• Lectures 11, Matrices -examples
• Saturday 3 July 2010
• Several slides courtesy Anirudha Jathar and
  Wikipedia

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Overview

• A quiz
• Handling images
• Representation of digital images
• Histogram
• Contrast enhancement
• Example program to calculate histogram of a small
  digital image

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A quiz

• Q. Currently, what activity do you propose to
  carry out within two weeks of the workshop
  conclusion, for the mandatory submission
• A. Design questions and answers for examinations
• B. Design quiz questions and answers
• C. Add lecture slides with examples
• D. Something different

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Digital images

• Digital images are a collection of pixel values
• These are arranged in an array (W x H)
• Each pixel value can be represented by
• 1 bit (m mono colour, e.g. black and white)
• 8 bits (g gray scale 0 black to 255 white)
• 24 bits (c Red, Blue, Green, each one byte)
• One can have 16 million colours!
• Capacity of a human eye is limited to a
• small range from 200 to 2000 colours

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Digital images ...

• While storing information about an image in a
  file, we mainly need values of Width, Height, the
  type of colours present, and values for each
  pixel
• Images such as black and white fingerprints have
  small size (500 x 300)
• For large images, compression is mandatory to
  keep the file size within limits
• 12 M pixel camera can produce 36 M bytes image
• Compression can be either lossy or lossless
• Several file formats have evolved
• raw, png, bmp, tiff, giff, jpeg, xmp
• Refer to wikipedia (Image_file_formats)

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Images and histograms

• Pixel values of digital images can be read in a
  matrix for further processing
• Each picture point (pixel) has an associated
  tonal value
• For grayscale images, the value range is 0-255
• 0 Black, 255 White
• Thus each element of such an image matrix would
  contain a value which can be of the type/size
  short int or char (1 byte)
• Histogram indicates how many pixels in an image
  have the same value

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A sample image 8 pixel x 8 pixel
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Pixel values in the sample image
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Histogram values

• Val n Val n Val n Val n
  Val n
• 52 1 64 2 72 1 85 2
  113 1
• 55 3 65 3 73 2 87 1
  122 1
• 58 2 66 2 75 1 88 1
  126 1
• 59 3 67 1 76 1 90 1
  144 1
• 60 1 68 5 77 1 94 1
  154 1
• 61 4 69 3 78 1 104 2
• 62 1 70 4 79 2 106 1
• 63 2 71 2 83 1 109 1

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Cumulative Distribution Function (cdf)

• V c V c V c V c V c
• 52 1 64 19 72 40 85 51 113 60
• 55 4 65 22 73 42 87 52 122 61
• 58 6 66 24 75 43 88 53 126 62
• 59 9 67 25 76 44 90 54 144 63
• 60 10 68 30 77 45 94 55 154 64
• 61 14 69 33 78 46 104 57
• 62 15 70 37 79 48 106 58
• 63 17 71 39 83 49 109 59

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Histogram equalization

• The histogram equalization formula
• Equalization formula for example image

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Histogram equalization

• For example, the cdf of 78 is 46

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Pixel values after histogram equalization
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Enhancement of Contrast
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Original Picture for comparison
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Another grayscale picture
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Histogram and cdf
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Equalized histogram and cdf
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Picture with enhanced contrast
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Original picture for comparison
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Program to calculate histogram

• includeltiostreamgt
• using namespace std
• int main()
• int i, j, npix
• int image500500, histogram256
• / we assume that the image data is contained
  in a text file "image.txt in a suitable format
• Also, we will use command line redirection to
  read data from this file
• /

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Histogram

• cin gtgt npix // number of pixels
• //read image pixel values in the matrix
• for(i0 ilt npix i)
• for(j0 j lt npix j)
• cin gtgt imageij
• cout ltlt imageij ltlt " "
• cout ltlt "\n"

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Histogram

• // set histogram counts to zero
• //
• for(i0 ilt 256 i) histogrami 0
• // Calculate histogram values
• for(i0 ilt npix i)
• for (j 0 j lt npix j)
• // based on the value of the pixel
• // increment the corresponding count
• // in the histogram array
• histogramimageij

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Histogram

• // print the histogram at non zero values
• cout ltlt "Histogram at non zero values is
• cout ltlt "\n"
• for (i0 ilt256 i)
• if (histogrami !0)
• cout ltlt i ltlt " " ltlt histogrami ltlt
  "\n"

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Histogram

• // find the maximum value in the histogram
• int imax, max 0
• for (i0 ilt256 i)
• if (histogrami gt max) max histogrami
• cout ltlt "Maximum histogram value " ltlt max
• cout ltlt occurs at ltlt "\n"
• // Print the grey levels at which max value
  occurs
• for(i0 ilt256 i)
• if (histogrami max) cout ltlt i ltlt " "
• return 0

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Image of a finger print
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• THANK YOU

28

• Question, From GEC Thrisur
• Can we return structure from the function ?

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• Question, From PSG Coimbatore
• Does C support function overloading ?

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• Question, From PSG Coimbatore
• Why is C, C generally use to design and develop
  
• an operating system ?

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• Question, From NIT, Kurukshetra
• What is the application of bit wise operators ?

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• Question, From GEC Thrisur
• What is the maximum dimension possible for a
  multi dimension array ?

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• Question, From GEC Thrisur
• Earlier Pascal was use to discuss programming
• methodology, later why its turn to C ?

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• Question, From PSG Coimbatore
• If C is not supporting function overloading mean
  how it is possible to use different number of
  scanf with different argument ?

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• Question, From NIT Kurukshetra
• When we declare float instruct and why scanning
  
• value, It will display floating point abnormal
  
• termination error ?

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• Question, From NIT Kurukshetra
• Is cin and cout return any value?

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• Question, From NIT Jalandhar
• What are macros and why they are taking lesser
  time during compilation?