Advance Digital Image Processing

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ADVANCE DIGITAL IMAGE 3710403
FREE PDF 3710403
Code: 3710403 Credits: 5 Semester 1 EACE

Advance Digital Image Processing

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

Advance Digital Image Processing Syllabus — Unit-wise Content

The official GTU curriculum for Advance Digital Image Processing (subject code 3710403) as prescribed for EACE · Semester 1 divides the course into 6 units, covering 51 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 (3710403)

Unit 1 Basic image processing operations

3 lecture hours

  • Point Operators
  • Group operators
  • Other statistical Operators
  • Mathematical morphology

Unit 2 Low- level feature extraction ( including edge detection)

6 lecture hours

  • First-order edge detection operators
  • Second- order edge detection operators
  • Other edge detection operators
  • Comparison of edge detection operators
  • Phase Congruency
  • Localized feature extraction
  • Detecting image curvature
  • Describing image motion

Unit 3 Feature extraction by shape matching

6 lecture hours

  • Thresholding and subtraction
  • Template matching
  • Hough transform (HT)
  • Generalized Hough transform (GHT)
  • Other extensions to the HT

Unit 4 Flexible shape extraction ( snakes and other techniques)

  • Deformable templates
  • Active contours (snakes)
  • Shape skeletonization
  • Flexible shape models: active shape and active appearance 6 Subject Code : 3710403 Subject Name : Advance Digital Image Processing https://syllabus.gtu.ac.in/ Page | 2

Unit 5 Object description

8 lecture hours

  • Boundary descriptions(Boundary and region
  • Chain codes
  • Fourier descriptors)
  • Region descriptors(Basic region descriptors

Unit 6 Introduction to texture description, segmentation and classification

9 lecture hours

  • What is texture
  • Texture description(Performance requirements
  • Structural approaches
  • Statistical approaches
  • Combination approaches)
  • Classification(The k- nearest neighbour rule
  • Other classification approaches)
  • Segmentation 10 7 3D Image Acquisition Volume imaging vs. sections
  • Basics of reconstruction
  • Algebraic reconstruction methods
  • Maximum entropy
  • Defects in reconstructed images
  • Imaging geometries
  • Three-dimensional tomography
  • High resolution tomography 8 8 3D Image Visualization Sources of 3D data
  • Serial sections
  • Optical sectioning Sequential removal Stereo
  • 3D data sets
  • Slicing the data set, Arbitrary section planes
  • The use of color
  • Volumetric display
  • Stereo Viewing
  • Special display hardware
  • Ray tracing
  • Multiply connected surfaces
  • Image processing in 3D, Measurements on 3D images

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