Teaching

CSPE77: Image Processing

B. Tech. 5th Semester (2020-21)
Dr. G. K. Verma



Course Learning Objectives

Image Processing is a major course in the computer science major, designed to teach students the fundamentals of digital image processing on the computer. The primary objective of this course is to introduce students to basic principles of digital images, image data structures, and image processing algorithms. Emphasis is on the general principles of image processing. Students learn to apply material by implementing and investigating image processing algorithms in Matlab and optionally on Android mobile devices.

Course outcomes

1.      Acquire the fundamental concepts of a digital image processing system

2.      Apply knowledge of various mathematical tools used for 1D and 2D signal analysis and processing

3.      Analyze 2D signals in the spatial and frequency domain.

4.      Design and implement algorithms for digital image processing operations.

5.      Ability to apply image processing techniques to solve various real time problems.

 

 



Grading

  • Participation: 10 percent
  • Assignments/ Quiz/ project: 20 percent
  • Midterm exam: 30 percent
  • Final exam: 50 percent


Instructional Format

The course will be taught in ''online classroom'' format. You may be provided a pre-recorded lectures, edited into shorter topical modules, and supplemented by quiz questions for reinforcement. Lecture videos and quizzes are released in due time during the semester. You must complete all lectures and quizzes to receive full credit. Students are expected to attend online lectures regularly.


Class Schedule (tentative)



The tentative schedules of the lectures are given below. Please check back on this page regularly for the most up-to-date class schedule.

Download Syllabus


Week

Lectures

Assignments

Study materials

Week 1

Introduction and Image Processing Examples

Point Operations

Histograms

Assignment 1

Slides

Notes

Week 2

Color Science, Color Balancing

Image Segmentation, Region Processing

Assignment 2

Slides

Notes

Week 3


Morphological Image Processing

Assignment 3

Slides

Notes

 



Popular Textbooks and Reading Material Links

Textbooks:

  1. R. C. Gonzales, R. E. Woods, "Digital Image Processing", 4th Edition, Pearson, 2018
  2. William K. Pratt, "Introduction to Digital Image Processing", CRC Press, 2013  

Software-Centric Textbooks:

  1. R. C. Gonzales, R. E. Woods, S. L. Eddins, "Digital Image Processing using MATLAB", 2nd Edition, Gatesmark Publishing, 2009
  2. A. Kaehler, G. Bradski, "Learning OpenCV 3", O'Reilly Media, 2017

Journals and Conference Proceedings:

  1. IEEE Transactions on Image Processing (TIP)
  2. IEEE International Conference on Image Processing (ICIP)
  3. IEEE Computer Vision and Pattern Recognition (CVPR)

 

COURSERA

https://www.coursera.org/courses?query=image%20processing

NPTEL

https://nptel.ac.in/courses/117/105/117105079/

https://nptel.ac.in/courses/117/105/117105135/

SWAYAM

https://swayam.gov.in/nd1_noc19_cs58/preview

 






SEMESTER

COURSE

Remarks


Fall, 2018

[UG] Image Processing [COT-447] (3-3-0) [1,2,3]

Syllabus

[UG] Database Systems Pr. [COT-313]

Lab Manual 

 

Spring, 2018

[PG] Natural Language Processing [COE-530]

  Syllabus 

[UG] Unix & Linux Programming [COT-218] & [IT-214]

  Syllabus 

Fall, 2017

[UG] Image Processing [COT-447] (3-3-0)

Syllabus 

[UG] Programming Methodology Pr. [COT-211]

Lab Manual 

Spring, 2017

[PG] & [PhD] Natural Language Processing [COE-530]

  Syllabus 

[UG] Unix & Linux Programming [COT-218] & [IT-214]

  Syllabus 



 
Fall, 2016

[UG] Data Structures [IT-205]

  Quiz Result
  Quiz with Answer

  Syllabus

[UG] Programming Methodology Pr. [COT-211]

 Syllabus   

 

Spring, 2016

[PG] Object Oriented Software Modeling [COE-504] (3-0-3)

Mid Term-I Qn ppr   Solution Mid Term-I

 Mid Term-II Qn ppr   Solution Mid Term-II

Quiz-I

[UG] Seminar  [COT-416]

Report Format           Evaluation format

 

Fall, 2015

[UG] Image Processing [COT-447] (3-3-0) [1,2,3]

 

[UG] Image Processing [COT-447] (3-3-0) [4,5,6]

 

 

Spring, 2015

[PG] Image Processing [COT-447] (3-3-0) [1,2,3]

 

[PG] Machine Learning []

 


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