8th Sem, C&C

Digital Image Processing C&C 8th Sem Syllabus for BE 2017 Regulation Anna Univ (Professional Elective IV)

Digital Image Processing C&C 8th Sem Syllabus for BE 2017 Regulation Anna Univ (Professional Elective IV) detail syllabus for Computer & Communication Engineering (C&C), 2017 regulation is collected from the Anna Univ official website and presented for students of Anna University. The details of the course are: course code (EC8093), Category (PE), Contact Periods/week (3), Teaching hours/week (3), Practical Hours/week (0). The total course credits are given in combined syllabus.

For all other c&c 8th sem syllabus for be 2017 regulation anna univ you can visit C&C 8th Sem syllabus for BE 2017 regulation Anna Univ Subjects. For all other Professional Elective IV subjects do refer to Professional Elective IV. The detail syllabus for digital image processing is as follows.

Course Objective:

  • To become familiar with digital image fundamentals
  • To get exposed to simple image enhancement techniques in Spatial and Frequency domain.
  • To learn concepts of degradation function and restoration techniques.
  • To study the image segmentation and representation techniques.
  • To become familiar with image compression and recognition methods

Unit I

For complete syllabus and results, class timetable and more pls download iStudy. Its a light weight, easy to use, no images, no pdfs platform to make students life easier.

Unit II

Image Enhancement
Spatial Domain: Gray level transformations – Histogram processing – Basics of Spatial FilteringSmoothing and Sharpening Spatial Filtering, Frequency Domain: Introduction to Fourier TransformSmoothing and Sharpening frequency domain filters – Ideal, Butterworth and Gaussian filters, Homomorphic filtering, Color image enhancement.

Unit III

Image Restoration
Image Restoration – degradation model, Properties, Noise models – Mean Filters – Order Statistics -Adaptive filters – Band reject Filters – Band pass Filters – Notch Filters – Optimum Notch Filtering -Inverse Filtering – Wiener filtering

Unit IV

For complete syllabus and results, class timetable and more pls download iStudy. Its a light weight, easy to use, no images, no pdfs platform to make students life easier.

Unit V

Image Compression and Recognition
Need for data compression, Huffman, Run Length Encoding, Shift codes, Arithmetic coding, JPEG standard, MPEG. Boundary representation, Boundary description, Fourier Descriptor, Regional Descriptors – Topological feature, Texture – Patterns and Pattern classes – Recognition based on matching.
TOTAL 45 PERIODS

Course Outcome:

At the end of the course, the students should be able to:

  • Know and understand the basics and fundamentals of digital image processing, such as digitization, sampling, quantization, and 2D-transforms.
  • Operate on images using the techniques of smoothing, sharpening and enhancement.
  • Understand the restoration concepts and filtering techniques.
  • Learn the basics of segmentation, features extraction, compression and recognition methods for color models.

Text Books:

  1. Rafael C. Gonzalez, Richard E. Woods, Digital Image Processing, Pearson, Third Edition,
  2. .

  3. Anil K. Jain, Fundamentals of Digital Image Processing, Pearson, 2002.

References:

  1. Kenneth R. Castleman, Digital Image Processing, Pearson, 2006.
  2. Rafael C. Gonzalez, Richard E. Woods, Steven Eddins, Digital Image Processing using MATLAB, Pearson Education, Inc., 2011.
  3. D,E. Dudgeon and RM. Mersereau, Multidimensional Digital Signal Processing, Prentice Hall Professional Technical Reference, 1990.
  4. William K. Pratt, Digital Image Processing, John Wiley, New York, 2002
  5. Milan Sonka et al Image processing, analysis and machine vision, Brookes/Cole, Vikas Publishing House, 2nd edition, 1999

For detail syllabus of all other subjects of BE C&C, 2017 regulation do visit C&C 8th Sem syllabus for 2017 Regulation.

Dont forget to download iStudy for latest syllabus and results, class timetable and more.

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