VL4009 VLSI Architectures for Image Processing Syllabus:

VL4009 VLSI Architectures for Image Processing Syllabus – Anna University PG Syllabus Regulation 2021

COURSE OBJECTIVES:

 The students will be able to acquire knowledge on image and video processing algorithms
 The students will be able to acquire knowledge on design of VLSI architectures.

UNIT I IMAGE PROCESSING ALGORITHMS AND ARCHITECTURES

Image Processing Tasks – Low Level Image Processing Operations – Intermediate Level Operations Image Processor Architecture: Requirements and Classification – Uni and Multi Processors – MIMD Systems – SIMD Systems – Pipelines – Design Aspects of Real Time Low Level Image Processors – Design Method for Special Architectures

UNIT II 3D IMAGE PROCESSING

Overview of 3D Image – Types and Characteristics of 3D Image Processing – Examples of 3D Image Processing, Continuous and Digitized Images, Models of Image Operations, Algorithm of Image Operations – Smoothing Filter – Difference Filter – Differential Features of a Curved Surface – Region Growing.

UNIT III 3D BINARY IMAGE PROCESSING

Introduction- Labeling of a Connected – Shrinking- Surface Thinning and Axis Thinning-Distance Transformation and Skeleton-Border Surface Following-Knot and Link – Voronoi Division of a Digitized Image-Algorithms for Processing Connected Components with Gray Values

UNIT IV PIPELINED, 2D AND 3D IMAGE PROCESSING ARCHITECTURES

Architecture of a Cellular Logic Processing Element – Second Decomposition in Data Path and Control – Real Time Pipeline for Low Level Image Processing – Design Aspects of Image Processing Architectures – Implementation of Low Level 2D and 3D and Intermediate Level Algorithms

UNIT V VLSI SYSTEMS FOR IMAGE PROCESSING

Concurrent Systems for Image Analysis- VLSI Wave front Arrays for Image Processing-Curve Detection in VLSI-Design of VLSI Based Multicomputer Architecture for Dynamic Scene Analysis VLSI-Based Image Resampling for Electronic Publishing

TOTAL:45 PERIODS

PRACTICAL EXERCISES: 30 PERIODS

1. Convert a 2D Image to 3D Image.
2. Perform Urinary, Binary Image Operations and Monotonic, Shift, Point, Shift-Invariant Operators for 2D Image.
3. Obtain a CT Scan Image , Perform The Following
a. Smooth Filter
b. Detection Filter
c. Morphological Filter
d. Region Growing
4. Perform Surface Thinning and Axis Thinning, Distance Transformation and Skeleton, Voronoi Division of a Digitized Image

TOTAL:30+45=75 PERIODS

COURSE OUTCOMES:

Upon Completion of The Course, Students Will Be Able to Demonstrate An Ability to
CO1:Analyze Various Architectures to Realize Image Processing Algorithms and Explain The 3D Image Processing Algorithms
CO2:Explore Various Processing Techniques of Image and Design Different Architectures for Image Processing.
CO3: Analyze various pipelined hardware architecture for 2D and 3D Image processing
CO4: Realize binary image processing algorithm in VLSI systems
CO5: Implement filter techniques in 2D and 3D image.

REFERENCES

1. Pieter Jonker, “Morphological Image Processing: Architecture and VLSI Design”, Springer, First Edition, 1992.
2. Junichiro Toriwaki · Hiroyuki Yoshida, “Fundamentals of Three-Dimensional Digital Image Processing”, Springer 2009.
3. King-Sun Fu, “VLSI for Pattern Recognition and Image Processing”, Springer-Verlag, 1984.