Advance Topics in Signal and Image Processing

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ADVANCE TOPICS IN 2744101
FREE PDF 2744101
Code: 2744101 Credits: 4 Semester 4 EAC(

Advance Topics in Signal and Image Processing

Get the full GTU study material, English & Gujarati textbook PDFs, syllabus curriculum, and solved previous year question papers.

Advance Topics in Signal and Image Processing Syllabus — Unit-wise Content

The official GTU curriculum for Advance Topics in Signal and Image Processing (subject code 2744101) as prescribed for EAC( · Semester 4 divides the course into 5 units, covering 39 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.

Download the official syllabus PDF (2744101)

Unit 1 Realization of digital Filters

8 lecture hours

  • Block diagram representation
  • based structure for IIR systems
  • Direct form realization of IIR filters
  • Direct-Form I, Direct Form-II Realization
  • cascade and parallel form realization of IIR filters
  • Transposed structure
  • Feedback in IIR System
  • Ladder and Lattice structure
  • conversion between Lattice structure and direct form structure

Unit 2 Theory and Design of FIR Filters

12 lecture hours

  • symmetric and asymmetric filters
  • Windowing Techniques
  • design of linear phase FIR filters
  • design of optimum Equi-Ripple linear phase FIR filters
  • Theory and Design of IIR Filters: Impulse Invariant method
  • Bi-linear transformation method
  • Butterworth filter approximation
  • chebyshev filter approximation
  • elliptical filters
  • Frequency transformation

Unit 3 Multirate Digital Signal Processing

12 lecture hours

  • sampling rate conversion methods
  • filter design and implementation for sampling rate alteration or conversion
  • sampling rate conversion by arbitrary factor

Unit 4 Image Representation and Feature Extraction

8 lecture hours

  • Chain Codes
  • Polygonal Approximations
  • Boundary segments
  • Feature vector and Vector spaces
  • Binary object features
  • Fourier Descriptors
  • Shape Number and Hierarchical Features
  • Historgram-based (Statistical ) Features
  • Texture features
  • Hough Transform

Unit 5 Visual Pattern Recognition

8 lecture hours

  • Design and Implementation of a Visual Pattern Classifier
  • Patterns and Pattern Classes
  • Data Preprocessing
  • Training and Test Sets
  • Confusion Matrix
  • Hit Rates
  • False Alarm Rates, and ROC

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