COMPUTER VISION & IOT LAB

Paper Code: 
DBDA 512 A
Credits: 
3
Periods/week: 
6
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 (COs). 

Course Outcome (at course level)

Learning and teaching strategies

Assessment Strategies 

 

On completion of this course, the students will:

CO251. Implementation of image processing concepts.

CO252. Perform image segmentation on real life problems.

CO253. Perform image recognition on real life problems.

CO254. Design circuit using raspberry pi and sensors.

CO255. Analyse the outcomes of circuits.

Approach in teaching.

Interactive Lectures, Group Discussion, Tutorials, Case Study

 

Learning activities for the students.

Self-learning assignments, Machine Learning exercises, presentations

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

 

 

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.
    • 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
    • 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.

 

  • Simulate a circuit using sensor (image, gas and temperature) and Raspberry Pi.

 

REFERENCES: 

 E RESOURCES

  •  NPTEL: Deep Learning for Computer Vision, IIT Hyderabad : https://nptel.ac.in/courses/106106224
  • Image processing by Saikiran Panjala, Slideshare: https://www.slideshare.net/MadhushreeGhosh3/image-processing-76619758

 

JOURNALS.

  • Journal of Real-Time Image Processing (JRTIP) springer: https://www.springer.com/journal/11554
  • IEEE Transactions on Image Processing: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=83

 

 

 

Academic Year: 
2023-24
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