5339B: Machine Vision Lab Syllabus for Automation & Robotics 6th Sem 2021 Revision SITTTR (Professional Elective-II)

Machine Vision Lab detailed syllabus for Automation & Robotics (RA) for 2021 revision curriculum has been taken from the SITTTRs official website and presented for the Automation & Robotics (RA) students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.

For Automation & Robotics 6th Sem scheme and its subjects, do visit Automation & Robotics (RA) 6th Sem 2021 regulation scheme. For Professional Elective-II scheme and its subjects refer to Automation & Robotics (RA) Professional Elective-II syllabus scheme. The detailed syllabus of machine vision lab is as follows.

Course Objectives:

• To introduce the student to OpenCV, especially for image processing.
• To Calibrate the camera and extract the intrinsic and extrinsic parameters of the camera
• To Find the edges in the image

Tools and Equipment

• Processors: Intel AtomR processor or IntelR Coreâ„¢ i3 processor.
• Disk space: 1 GB.
• Operating systems: Windows 7 or later, macOS, and Linux.
• Software: PyCharm, OpenCV

Course Outcomes:

On completion of the course, the student will be able to:

1. To Perform basic Image Handling and Processing operations on the image.
2. To perform various techniques of image enhancement, reconstruction, compression and segmentation
3. To perform Edge Detection, Line Detection and Corner Detection.
4. To perform Camera Calibration

Module 1:

1. Reading, displaying, and writing an image using OpenCV.
2. Convert the image to another format using OpenCV
3. Perform the image resizing using OpenCV.
4. Convert a colored image into a grayscale image using OpenCV.
5. Scaling, rotation and shifting operation on the image using OpenCV.
6. Play a video using OpenCV.
7. Extract images from the video.

Module 2:

1. Perform scaling, rotation and shifting operations on an image using OpenCV()
2. Perform image reflection on an image using OpenCV().
3. Perform Image shearing on an image using OpenCV().
4. Apply the affine transformation on an image using OpenCV().

Module 3:

1. Compute the edge detection using Sobel, Prewitt and canny operator.
2. Implement the Harris Corner detector algorithm to determine the corner in the image.
3. Implement the Harris Corner Detector algorithm without the inbuilt OpenCV() function.
4. Detect the line using Hough Transform

Module 4:

1. Perform the camera calibration and compute the intrinsic and extrinsic parameters of the camera.

Online Resources

1. OpenCV Python Tutorial -GeeksforGeeks
2. OpenCV-python-tests/cameraCalibration.py at master · jagracar/OpenCV-python-tests · GitHub
3. OpenCV: Image Gradients
4. https://github.com/

For detailed syllabus of all other subjects of Automation & Robotics, 2021 revision curriculum do visit Automation & Robotics (RA) 6th Sem subject syllabuses for 2021 revision.

To see the syllabus of all other branches of diploma 2021 revision curriculum do visit SITTTR diploma all branches syllabus..

To see the results of Automation & Robotics of diploma 2021 revision curriculum do visit SITTTR diploma results..

For all Automation & Robotics academic calendars, visit Automation & Robotics all semesters academic calendar direct link.