Department of Computer Science and Engineering

Module 1 (10 (T) + 7(P) Hours)

Internet and its architecture, Client Server Networking - Creating an Internet Client, Application Protocols and http, Presentation aspects html, CSS and Java script, Creating a web server, Serving Dynamic Content- CGI – overview of technologies like PHP – applets – JSP. Implementation examples.
Module 2 (10 (T) + 7(P) Hours)

Web server architecture, Programming threads in C, Shared memory synchronization, Performance measurement and workload models. Comparison using existing benchmarks.

Module 3 (10 (T) + 7(P) Hours)

Web development frameworks – Detailed study of one open source web framework - Ruby Scripting, Ruby on rails – Design, Implementation and Maintenance aspects.

Module 4 (12 (T) + 7(P) Hours)

Service Oriented Architecture – SOAP. Web 2.0 technologies. – AJAX. Development using Web2.0 technologies. Introduction to semantic web.

References:

1. 
   Dave Thomas, with Chad Fowler and Andy Hunt. Programming Ruby: The Pragmatic Programmer's Guide, 3/e, Pragmatic Programmers, May 2008.
   
2. 
   Balachander Krishnamurthy and Jennifer Rexford. Web Protocols and Practice: HTTP/1.1, Networking Protocols, Caching, and Traffic Measurement, Addison Wesley Professional, 2001.
   

CS4043 IMAGE PROCESSING

Pre-requisite: Nil

L	T	P	C
3	0	2	4

Total Hours: 70 Hrs  

Module 1 (10 (T) + 7(P) Hours)

Fundamentals of Image processing: Digital image representation, Elements of Digital image processing systems, Image model, Sampling and Quantization, Basic relations between pixels.

Image transforms: One dimensional Fourier transform, Two dimensional Fourier transform, Properties of two dimensional Fourier transform. Walsh transform, Hadamard transform, Discrete cosine transform, Haar transform, Slant transform.
Module 2 (10 (T) + 7(P) Hours)

Image enhancement techniques: Spatial domain methods, Frequency domain methods, Intensity transform, Histogram processing, Image subtraction, Image averaging, Smoothing filters, Sharpening filters, Spatial masks from frequency domain.
Module 3 (10 (T) + 7(P) Hours)

Image Segmentation: Thresholding: Different types of thresholding methods, Point detection, Edge detection: Different types of edge operators, Line detection, Edge linking and boundary detection, Region growing, Region splitting, Region Merging.
Module 4 (12 (T) + 7(P) Hours)

Image Data Compression: Fundamentals, Compression models, Error free compression, Lossy Compression, Image compression standards.

Applications of Image Processing: Medical imaging, Robot vision, Character recognition, Remote Sensing.
References:

1. 
   R.C.Gonzalez and R.E.Woods, Digital Image Processing, Addison-Wesley, 2007.
   
2. 
   Milan Sonka, Vaclav Hlavac and Roger Boyle, Image Processing, Analysis, and Machine Vision, 2/e, PWS Publishing, 1999.
   

CS4044 PATTERN RECOGNITION

Pre-requisite: Nil

L	T	P	C
3	0	2	4

Total Hours: 70 Hrs  

Module 1 (10 (T) + 7(P) Hours)

Introduction: Machine Perception , Pattern Recognition Systems, The Design Cycle, Learning and Adaptation.

Baye’s Decision Theory: Bayes Decision Theory, Minimum Error rate Classification, Classifiers, Discriminant functions and Decision Surfaces, Normal Density, Discriminant functions for the Normal Density, Bayes Decision Theory for Discrete features
Module 2 (10 (T) + 7(P) Hours)

Maximum Likelihood and Bayesian Parameter Estimation :Maximum Likelihood Estimation, Bayesian Estimation, Bayesian Parameter Estimation, Gaussian Case and General Theory.

Non Parametric Techniques: Density Estimation, Parzen Windows , K- Nearest Neighbor Estimation,NN rule, Metrics and NN Classification, Fuzzy Classification
Module 3 (10 (T) + 7(P) Hours)

Linear Descriminant Functions : Linear Discriminant Functions and Decision Surfaces, Generalized Discriminant Functions, The two-category linearly separable case , Minimizing the perceptron criterion function, relaxation procedures, non- separable behavior, Minimum Squared- Error procedures.
Module 4 (12 (T) + 7(P) Hours)

Multi Layer Neural Networks : Feed-forward Operation, Classification, Back – propagation Algorithm, Error Surfaces, Back-propagation as Feature mapping.
References:

1. 
   R. O. Duda, P. E. Hart and D. G. Stork, Pattern Classification, John-Wiley, 2004.
   
2. 
   J. T. Tou and R. C. Gonzalez, Pattern Recognition Principles, Tou and Gonzalez, Wiley, 1974.
   

CS4045 MEDICAL IMAGE PROCESSING

Pre-requisite: Nil

L	T	P	C
3	0	2	4

Total Hours: 70 Hrs