Computer Vision and IoT Lab

Paper Code: 
25DBDA512A
Credits: 
03
Periods/week: 
06
Max. Marks: 
100.00
Objective: 

This course will enable students to

1. Perform image processing

2. Understand the  circuit designing through Raspberry pi.

 

Course Outcomes: 

Course

Learning outcome

(at course level)

Learning and teaching strategies

Assessment

Strategies

Course

Code

Course

Title

CO301.      Implement image     transformation techniques   to   prepare images for analysis. CO302.           Perform image segmentation on real  life problems. CO303.            Design solution    for    real    life problems   using   image recognition techniques. CO304. Design   circuit using   raspberry pi  and sensors.

CO305.   Analyse    the outcomes of circuits. CO306.      Contribute

effectively in course-specific interaction

Approach in teaching:

 

Interactive Lectures, Discussion, Demonstration,

 

Learning activities for the students:

 

Self-learning assignments, Practical questions

ns

Class test, Semester end examinations, Quiz, Practical Assignments, Presentation.

 

 

 

 

 

 

 

 

 

 

25DBDA 512

A

 

 

 

 

 

 

 

 

 

Computer Vision and IoT Lab (Practical)

 

Practical  based on following topics.

    Computer Vision. -

1.   Simulation and  Display of an  Image, Negative of an  Image(Binary & Gray Scale)

2.     Implementation of Relationships between Pixels

3.     Implementation of Transformations of an  Image

4.     Contrast stretching of a low contrast image, Histogram, and  Histogram Equalization.

5.   Display of bit planes of an  Image

6.     Display of FFT(1-D & 2-D) of an image

7.     Computation of Mean,  Standard Deviation, Correlation coefficient of the  given  Image

8.   Implementation of Image Smoothening Filters(Mean and  Median  filtering  of an Image)

9.   Implementation of image sharpening filters  and  Edge  Detection using  Gradient Filters

10.   Image Compression by DCT,DPCM, HUFFMAN coding

11. Image segmentation

12. Image recognition

      IOT.

  1. Working   with   Raspberry  Pi  3  Model  -  Installing   OS  and   Designing   Systems  using Raspberry pi  -  Configuring  Raspberry Pi for  VNC Connection  -  Getting introduced to Linux  OS Basic  Linux  commands and  uses -  Getting   Started with  Python -  Interface sensor and  Actuator with Raspberry Pi
  2. Start  Raspberry Pi and  try  various  Linix commands in  command terminal  window.  ls, cd,  touch, mv,  rm,  man, mkdir,  rmdir,  tar,  gzip,  cat,  more, less,  ps,  sudo, cron,  chown, chgrp, ping etc
  3. Simulate a circuit using  sensor (image, gas  and  temperature) and  Raspberry Pi.

 

ESSENTIAL READINGS: 

1.     Lakhwani, Kamlesh, Hemant Kumar  Gianey,  Joseph Kofi Wireko,  and  Kamal Kant Hiran.  Internet of Things  (IoT): Principles, paradigms and  applications of IoT.  Bpb Publications, 2020.

2.   Szeliski,  Richard. Computer vision: algorithms and  applications. Springer Nature, 2022.

 

REFERENCES: 

SUGGESTED READINGS:

1.     Kaehler, Adrian,  and  Gary Bradski.  Learning OpenCV 3: computer vision in C++ with the  OpenCV library.  " O'Reilly Media,  Inc.",  2016.

2.     Misra, Sudip,  Chandana Roy, and  Anandarup Mukherjee. Introduction to industrial internet of things and  industry 4.0.  CRC Press, 2021

e RESOURCES   

1.     NPTEL: Deep  Learning for Computer Vision, IIT Hyderabad :

https://nptel.ac.in/courses/106106224

2.    Image processing by Saikiran  Panjala, Slideshare:

https://www.slideshare.net/MadhushreeGhosh3/image-processing-76619758

JOURNALS.

1.    Journal of Real-Time Image Processing (JRTIP)  springer:https://www.springer.com/journal/11554

2.    IEEE Transactions on Image Processing:https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=83

 

Academic Year: 
2025-26
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