B.E. (Automation and Robotics) Machine Vision System Lab Syllabus - Mumbai University 2026
The University has moved this degree onto NEP 2020 one year at a time. The first and second years are NEP 2020 syllabi; the third and fourth years are still examined on the REV-2019 'C' Scheme, which is what the University sets for them this year.
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Syllabus for Machine Vision System Lab
Module 1: Handling Files, Cameras, and GUIs
- Basic I/O scripts, Reading/writing an image file, converting between an image and raw bytes, Accessing image data with numpy. array, Reading/writing a video file, Capturing camera frames, Displaying images in a window, Displaying camera frames in a window.
Module 2: Processing Images with Open CV3
- Converting between different colour spaces, The Fourier Transform, High pass filter, Low pass filter
Module 3: Edge detection with Canny
- Contour detection, Contours – bounding box, minimum area rectangle, and minimum enclosing circle, Contours – convex contours and the Douglas-Peucker algorithm, Line and circle detection
Module 4: Depth Estimation
- Capturing frames from a depth camera Creating a mask from a disparity map Masking a copy operation Depth estimation with a normal camera
Module 5
- Object segmentation using the Watershed and GrabCut algorithms, Example of foreground detection with GrabCut, Image segmentation with the Watershed algorithm
Module 6
- Detecting and Recognizing Faces Conceptualizing Haar cascades Getting Haar cascade data Using OpenCV to perform face detection Performing face detection on a still image
Module 7: Performing face detection on video
- Performing face recognition Generating the data for face recognition Recognizing faces Preparing the training data Loading the data and recognizing faces Performing an Eigenfaces recognition
Module 8: Retrieving Images and Searching
- Using Image Descriptors, Feature detection algorithms, Defining features Detecting features – corners Feature extraction and description using DoG and SIFT Anatomy of a key point
Module 9: Detecting and Recognizing Objects Object detection and recognition techniques HOG descriptors
- The scale issue The location issue Non-maximum (or non-maxima) suppression Support vector machines People detection
Module 10: Creating and training an object detector Bag-of-words BOW in computer vision Detecting cars in a scene
Reproduced from the University of Mumbai syllabus for B.E. (Automation and Robotics) under REV-2019 'C' Scheme, in force from the academic year 2024-25. Wording is as printed in that syllabus. Module numbering is as printed there too.
The complete syllabus
This subject is cut from the University circular for its year. Open a document here if you want the whole thing rather than a single subject.