Page 65 - REC :: All Dept Open Electives

TEXT BOOKS:

1. Thomas L Floyd, "Electronic Devices" 10th Edition Pearson Education Asia 2018.
2. Philp Hoff, "Consumer Electronics for Engineers" - Cambridge University Press.1998.
3. Jordan Frith, ―Smart phones as Locative Media ", Wiley. 2014.
4. Dennis C Brewer, ―Home Automation", Que Publishing 2013.
5. Thomas M. Coughlin, "Digital Storage in Consumer Electronics", Elsevier and Newness 2012.

OEC1703 DIGITAL IMAGE PROCESSING AND ITS APPLICATIONS L T P C
3 0 0 3

OBJECTIVES: The student should be made to:
 Learn digital image fundamentals.
 Be exposed to simple image processing techniques.
 Be familiar with restoration and segmentation techniques
 Understand lossy and loss less compression techniques
 Learn to represent image in form of features

UNIT I DIGITAL IMAGE FUNDAMENTALS 8

Introduction – Origin – Steps in Digital Image Processing – Components – Elements of Visual
Perception – Image Sampling and Quantization

UNIT II IMAGE ENHANCEMENT AND RESTORATION 10

Spatial Domain: Gray level transformations – Histogram processing – Basics of Spatial Filtering–
Smoothing and Sharpening Spatial Filtering – Frequency Domain: Smoothing and Sharpening
frequency domain filters –. Noise models – Mean Filters – Inverse Filtering – Wiener filtering

UNIT III IMAGE SEGMENTATION AND COMPRESSION 9

Segmentation: Detection of Discontinuities–– Region based segmentation. Compression: Fundamentals
– Image Compression models – Error Free Compression – Variable Length Coding –Lossless Predictive
Coding – Lossy Compression – Lossy Predictive Coding.

UNIT IV IMAGE REPRESENTATION 9

Boundary representation – Chain Code – Polygonal approximation, signature, boundary segments –
Boundary description – Shape number – Fourier Descriptor, moments- Regional Descriptors –
Topological feature, Texture

UNIT V IMAGE RECOGNITION AND MORPHING 9

Patterns and Pattern classes - Recognition based on decision theoretic methods. Image morphing-
Recent advances in image morphing. Detection of morphed face image- any case study.

TOTAL= 45 PERIODS

Curriculum and Syllabus | Open Electives | R 2017 | REC Page 65