B.E. (Biomedical Engineering) Biomedical Digital Image Processing Abbreviated As BDIP Syllabus - Mumbai University

This is the Third Year Biomedical Rev 2019 C Scheme syllabus under REV-2019 'C' Scheme, in force from the academic year 2021-22. The University has not yet published an NEP 2020 syllabus above Semester IV for this branch, and this is the scheme its examinations are set on.

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Syllabus for Biomedical Digital Image Processing (abbreviated as BDIP)

Semester 6 · Third Year Biomedical Rev 2019 C Scheme · 3 credits · 100 marks

Module 1

Basics of Image Processing: Image acquisition, processing, communication, display; electromagnetic spectrum; elements of visual perception - structure of the human eye, image formation in the eye, brightness adaptation and discrimination, image formation model, uniform and non-uniform sampling, quantization, image

Module 2

Image Enhancement: Spatial domain - point processing techniques, histogram processing, neighbourhood processing, frequency domain techniques, 2D-DFT, properties of 2D-DFT, low pass, high pass, noise removal, homomorphic filters, basics of colour image processing.

Module 3

Image Segmentation: Basic relationships between pixels, neighbours, adjacency, connectivity, regions, boundaries, distance measures; detection of discontinuities, point, line and edges, edge linking, Hough transform, thresholding based segmentation, region-based segmentation.

Module 4

Image Transforms & Image Compression: DFT, FFT, DCT, DST, Hadamard, Walsh, Haar, basis functions and basis images, introduction to wavelet transform, fundamentals of image compression models, lossless compression, RLE, Huffman, LZW and arithmetic coding techniques, lossy compression - IGS coding, transform coding, JPEG, JPEG 2000.

Module 5

Morphology, Representation and Description : Dilation, erosion, open, close, hit or-miss, boundary extraction, region filling, thinning and thickening; chain codes, polygonal approximations, signatures; fourier descriptors, moments.

Module 6

Feature Recognition and Classification: Object recognition and classification, components labelling, features, statistical classification, structural/syntactic classification, applications in medical image analysis

Text books

1 Digital Image Processing, Gonzalez and Woods - Pearson Education.
2 Fundamentals of Digital Image Processing, A.K. Jain – P.H.I.
3 Digital Image Processing and Analysis, Chanda Majumder - Printice Hall India.
1 Digital Image Processing for Medical Applications, Geoff Dougherty, Cambridge University Press, 2009..
2 Digital Image Processing, William Pratt - John Wiley. NPTEL/Swayam Course: Course: Digital Image Processing - NPTEL Lecture Videos by Prof. P.K. Biswas from IIT Kharagpur. http://www.nptelvideos.com/course.php?id=541 Theory Examination:

Reproduced from the University of Mumbai syllabus for B.E. (Biomedical Engineering) under REV-2019 'C' Scheme, in force from the academic year 2021-22. Wording is as printed in that syllabus. Module numbering is as printed there too.

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