Omar Al-Kadi's Homepage

Document Analysis & Recognition (Lecture notes*) [course syllabus]

• Ch1
• Ch2
• Ch3
• Ch4
• Ch5
• Ch6
• Ch7 & 8
• Ch9
• Ch10

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Weeks 15:

• Programming project submission (grading, guidelines)

 

Weeks 14:

• Exercises on Morphological operations (see example6, example7)
• Matlab implementation (example8)

 

Weeks 13:

• Exercises on DCT (see example5, mfile)

 

Weeks 11-12:

• Color Image Processing (Ch 6 slides 1-40 only)
• Matlab implementation (mfile4, example4, mfile5)
• Image Compression (Ch 7 slides 1-15 + example5)
• Quiz: take the quiz, click here.

 

Weeks 9-10:

• Ch5: Image Restoration (large file 118MB)
• Exercises, ex2&3_soln

 

Weeks 7-8:

• Frequency filtering:
  • One-Dimensional Fourier transform numerical example (example, cat2pol, example2)
  • Calculating 1-D Fourier transform and deriving magnitude and phase angle of frequency domain spectrum (mfile1, mfile2)
  • Two-Dimensional frequency domain filtering (mfile3)
• Quiz: take the quiz, click here.
• Project submission: upload your project by clicking here.

 

Weeks 5-6:

• Matlab implementation of the above spatial filters for image enhancement (pdf, mfile)
• Image spatial filtering simple example (pdf, pdf2).
• Incase if you experience difficulty in submitting your assignment3 to the e-learning platform (e.g. server down), you can upload your assignment here (use class code: rklj3yu). Due date is Thursday, March 26th at 5:00pm.
• Chapter 4 screencasts can be viewed and downloaded from the following url links:
  • • Ch4 Part 1 (Introduction to Frequency Domain Filtering)
    • Ch4 Part 2 (Frequency Domain Components)
    • Ch4 Part 3 (Low & High-pass Filters)
    • Ch4 Part 4 (Smoothing & Sharpening in Frequency Domain)

All 4 parts can be download in one piece. (large file 158MB)

 

Weeks 3-4:

Screencasts for image enhancement in spatial domain have been uploaded to the e-learning platform. You may also view and download the videos from the following links:

• Part 1 (Image smoothing and blurring – box and average filter)
• Part 2 (Noise removal – median filter)
• Part 3 (Image sharpening)
• Part 4 (Sobel filter and comprehensive example)

• Manipulating matrices (images) in MATLAB

Weeks 1-2:

• Connectivity operations (pdf, video)
• Distance measures (city block, max, and Euclidean distance)
• Bit-plane slicing
• Numerical example on histogram equalisation.

Exam results can be checked here. (NEW)

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(*Source textbook: R. Gonzalez, R. E. Woods, Digital Image Processing, 4th Ed.,Prentice Hall, 2018)