1. DATA Structures in JAVA

Fairfield University

School of Engineering

Course Name & Number: DATA Structures in JAVA CE ???

Instructor: Prof. D. Lyon

Home Phone:

Business Phone:

E-mail: lyon@DocJava.com

FAX: (203)877-4187

Instructor Assistance: (additional support prior to and/or after class)

Lecture Hours: 3 hours per week starting at 6:30PM

Lab Hours: 0 hours per semester

Course Description:

a study of data structures and algorithms. Topics include stacks, lists, queues, linked lists, trees, Binary Search Trees, B-trees, AVL-trees, reachability, Minimum Spanning Trees and Disjoint Sets, graph optimization.

PreReq: CS131

Learning Objectives:

After the student take this course, they will know how to write programs that divide the data structure into its specification (via interface) and subsequent implementation. The students will know how to think abstractly about data structures and be able to perform algorithm analysis. Students will have facility with linked lists, queues, trees, priority queues and hash tables. Students will be able to write recursive programs, and sorting algorithms.

This course requires substantial programming effort and emphasis is place on good software engineering practices.

Outcomes:

1. The students will learn the principles of Data Structures.

Expected learning outcomes:

a. Big-O rules

b. Data Structures (Stacks, Queues, Linked Lists, Trees, Hash Tables)

c. Recursion, sorting (shell sort, merge sort, quick sort)

2. The student will become proficient with the usage of the Java language.

Expected learning outcomes:

a. Demonstrates the ability to utilize Java in practical data structures

b. Uses appropriate object-oriented design patterns to solve problems.

After students take this course, they will know how to write programs that can use data structures. Finally, the students will make use of object-oriented design patterns and data structures in order to implement algorithms.

This course requires substantial programming effort and emphasis is place on good software engineering practices.

Outcomes:

When the course is done, Students will have deployed Java applications of their own design, on the web.

Performance Indicators:

Aside from the basics assessment procedures based on homeworks and tests, Students must obtain 75% or better on all tests. Additionally, students must perform at least 75% on the homeworks.

Textbook: DATA STRUCTURES & Problem Solving Using Java, by M. Weiss

Reference Material: Notes, as required.

Course Requirements:

All homework is to be submitted on time.

The course includes three reporting periods (exam, quiz, project, etc.) and a comprehensive final.

Topics :

1. Basic Java

2. Objects, Classes, and Packages

3. Inheritance

4. The AWT and Applets

5. Algorithm Analysis

6. Stacks and Queues (Part I)

7. Stacks and Queues (Part II) - Linked Lists

8. Infix Expression Evaluation

9. Binary Search Trees

10. AVL Trees

11. B-Trees

12 Priority Queues

• Operations and Applications

• The binary heap

• Linear-time construction

• Heapsort

• Insertion sort

• Quicksort

• Selection

• Lower Bounds

13 Graph Algorithms

• Graph Representation

• Topological Sort

• Unweighted Shortest Paths (breadth-first search) • Weighted Shortest Path (Dijkstra's algorithm)

14 Minimum Spanning Trees and Disjoint Sets • The Disjoint Set Problem

• Minimum Spanning Trees

• Kruskal's Algorithm

• The Union/Find Data Structure

Attendance Policy: Students are responsible to acquire notes and homework assignment from classmates in case of absence.

Weighted

Grading:

Midterm 1/3

Final Examination 1/3

Homework 1/3 includes tests, quizzes, projects, etc.

2. Digital Design I

Fairfield University

School of Engineering

Course Name & Number: Digital Design I EE 245 + EE 245L

Instructor: Prof. D. Lyon

Home Phone:

Business Phone:

E-mail: lyon@DocJava.com

FAX: (203)877-4187

Instructor Assistance: (additional support prior to and/or after class)

Lecture Hours: 3 hours per week starting at 6:30PM

Lab Hours: 0 hours per semester

Course Description:

Basic digital design principles. Boolean algebra. Combinational logic design with gates, MSI, LSI. Sequential logic design; register, counters, memory and PLD.
PreReq: EE 213

Learning Objectives:

After the student take this course, they will know how to perform elementary digital design.

This is a foundations course that enables students to be able to perform well in the follow-on course, Digital Design II.

Student knowledge of the basics culminated in being able to design and implement finite-state machines.

Outcomes:

1. The students will learn the principles of Digital Design.

Expected learning outcomes:

a. k-maps

b. Boolean Algebra

c. carry out a design using a simulator

2. The student will become proficient with a schematic capture simulator.

Expected learning outcomes:

a. Demonstrates the ability to implement a Finite State machine

b. Implement an open-ended word problem with the simulator.

After students take this course, they will know how to write implement and simulate their digital designs.

Performance Indicators:

Aside from the basics assessment procedures based on homeworks and tests, Students must obtain 75% or better on all tests. Additionally, students must perform at least 75% on the homeworks.

Textbook: Contemporary Logic Design, Katz

Reference Material: Notes, as required.

Course Requirements:

All homework is to be submitted on time.

The course includes three reporting periods (exam, quiz, project, etc.) and a comprehensive final.

Session #/Date Topic Text Chapter(s) Homework Assignment

Topics :

1 Introduction

2 Boolean Algebra

3 Applications of Boolean Algebra

4 K-maps

5 Multi-level Gate Networks, Nand and NOR gates •

6 Multiple-output networks, Mux's,

7 Decoders, ROMs and PLA's

8 Flip-flops

9 Counters and Sequential Nets

10 Analysis of Clocked Sequential Nets •

11 Derivation of State Graphs and Tables •

12 Nets for addition and subtraction

13 State Machines and State Machine Charts

Attendance Policy: Students are responsible to acquire notes and homework assignment from classmates in case of absence.

Weighted

Grading:

Midterm 1/3

Comprehensive Final Examination 1/3

Homework 1/3 (tests, quizzes, projects..)

3. Digital Design II

Fairfield University

School of Engineering

Course Name & Number: Digital Design II EE 245 + EE 245L

Instructor: Prof. D. Lyon

Home Phone:

Business Phone:

E-mail: lyon@DocJava.com

FAX: (203)877-4187

Instructor Assistance: (additional support prior to and/or after class)

Lecture Hours: 3 hours per week starting at 6:30PM

Lab Hours: 0 hours per semester

Course Description:

Computer architecture implemented using a hardware design language and PLDs. Students design, implement and program small RISC machines.

PreReq: EE 245

Learning Objectives:

After the student take this course, they will know how to implement and program a CPU using VHDL.

Students will understand CPU architectures, and how to program in VHDL.

Student knowledge of the basics culminated in being able to design and implement programmable finite-state machines.

Outcomes:

1. The students will learn the principles of Computer Architecture.

Expected learning outcomes:

a. broad understanding of computer architecture

b. Basic parts of a CPU

c. carry out a design using a PLD

2. The student will become proficient with VHDL.

Expected learning outcomes:

a. Demonstrates the ability to implement a RISC machine

b. Program an open-ended word problem with the RISC machine.

c. Perform Mealy sequential FSM design

d. Design serial accumlator elements

e. Design floating point elements

f. Design a microcontroller CPU

After students take this course, they will know how to design and implement CPUS of their own design. They will also know a little about machine language programming..

Performance Indicators:

Aside from the basics assessment procedures based on homeworks and tests, Students must obtain 75% or better on all tests. Additionally, students must perform at least 75% on the homeworks.

Textbook: Digital Systems Design using VHDL by Roth.

Reference Material: Notes, as required.

Course Requirements:

All homework is to be submitted on time.

The course includes three reporting periods (exam, quiz, project, etc.) and a comprehensive final.

Topics :

1 Intro to VHDL

2 Counter Design/Memory

3 Finite State Machine design

4 Computer Organization

5 Busing strategies

6 Finite State Machines for Simple CPU's

7 Controller Implementation

8 Jump counters

9 Branch sequencers

10 Reduction of State tables State Assignment

11 Design of Microcontroller

12 Nets for multiplication and division

13. Verification

14. Model optimizations

Attendance Policy: Students are responsible to acquire notes and homework assignment from classmates in case of absence.

Weighted

Grading:

Midterm 1/3

Final Examination 1/3

Homework 1/3 includes tests, quizzes, projects, etc.

4. Computer Networks

Fairfield University

School of Engineering

Course Name & Number: Computer Networks CE??

Instructor: Prof. D. Lyon

Home Phone:

Business Phone:

E-mail: lyon@DocJava.com

FAX: (203)877-4187

Instructor Assistance: (additional support prior to and/or after class)

Lecture Hours: 3 hours per week starting at 6:30PM

Lab Hours: 0 hours per semester

Course Description:

Operating system elements, multi-threading, command-line interpreters and monitors. Students write their own operating system, implemented in Java, using a virtual machine. New system commands are added to the JAVAOS. Students deploy a custom-built, distributed, multi-platform, thin-client operating system.
PreReq: Data Structures in Java

Outcomes:

1. The students will learn the principles of Network Programming.

Expected learning outcomes:

a. Servlets

b. RMI

c. Object Serialization

2. The student will become proficient with the mathematical tools for modeling traffic.

Expected learning outcomes:

a. Demonstrates the ability to model m/m/1 and m/g/1 queues

b. Simulate an Nth order Markov process.

After students take this course, they will know how to write implement and simulate models of traffic.

Performance Indicators:

Aside from the basics assessment procedures based on homeworks and tests, Students must obtain 75% or better on all tests. Additionally, students must perform at least 75% on the homeworks.

Textbook: Java Network Programming, by Hughes et. Al.

Reference Material: Notes, as required.

Course Requirements:

All homework is to be submitted on time.

The course includes three reporting periods (exam, quiz, project, etc.) and a comprehensive final.

Topics by week:

1. OSI seven layer model, and TCP/IP suite

2. Services (FTP, Telnet, Gopher, Finger, SMTP, SNMP, HTTP, DNS)

3. Introduction to Cryptography, (public key encryption, hash functions, signatures)

4. Java Security model (manager, resource, threads, network resources)

5. Introduction to streams (output, input, file and filter streams)

6. Filter streams (buffered input and output streams, memory I/O streams., Piped streams)

7 Client-side networks (getting web pages with sockets, posting output streams)

8 Server-side networking (echo server, non blocking server, chat server)

9. Data gram networking (UDP alarms, a UDP echo server, message streams).

10. Queuing theory, (M/M/1, simple traffic, Poisson arrivals).

11. Simulating a Markov process, predicting traffic

12. Remote method invocation

13. Building a white board server

14 Building a white board client

15 Monitoring traffic in the system and correlating with simulation.

Attendance Policy: Students are responsible to acquire notes and homework assignment from classmates in case of absence.

Weighted

Grading:

Midterm 1/3

Final Examination 1/3

Homework 1/3 includes tests, quizzes, projects, etc.

5. Operating Systems in Java

Fairfield University

School of Engineering

Course Name & Number: Operating Systems in Java CE??

Instructor: Prof. D. Lyon

Home Phone:

Business Phone:

E-mail: lyon@DocJava.com

FAX: (203)877-4187

Instructor Assistance: (additional support prior to and/or after class)

Lecture Hours: 3 hours per week starting at 6:30PM

Lab Hours: 0 hours per semester

Course Description:

PreReq: Data Structures in Java

Learning Objectives:

After the student take this course, they will know how to write Java programs that can perform network services. .

Students will understand the layers and protocols in the Internet and OSI models. Students will understand multi-threaded streaming, message routing, serialization and persistence.

Student knowledge of the basics culminated in being able to design and implement a client-server system.

Learning Objectives:

After the student take this course, they will know how to write Java programs that can perform operating system services. .

Students will understand the basic of operating systems. Students will design and implement their own operating system, with a web distribution requirement.

Student knowledge of the basics is culminated in the design of a thread management system, integrated into the JavaOS.

Outcomes:

1. The students will learn the principles of Operating System.

Expected learning outcomes:

a. Threads

b. Command Line Interpreters

c. Schedulers

2. The student will become proficient with the programming tools for implementing an operating system.

Expected learning outcomes:

a. Demonstrates the ability to add new system commands

b. Build a thread manager.

After students take this course, they will know how to design and implement an operating system.

Performance Indicators:

Aside from the basics assessment procedures based on homeworks and tests, Students must obtain 75% or better on all tests. Additionally, students must perform at least 75% on the homeworks.

Textbook: Inside the JAVAOS Operating System, by Saulpaugh et. Al.

Reference Material: Notes, as required.

Course Requirements:

All homework is to be submitted on time.

The course includes three reporting periods (exam, quiz, project, etc.) and a comprehensive final.

Topics by week:

1. Overview, JavaOS and the JDK, Computing models, major components

2. The database (The JavaOS System Database, JSD, Namespaces, trees and navigation)

3. The event system, consumer-producer ordering rules, threading, device events

4. Service loader, business cards, JavaOS configuration, service loader, client-server connections

5. Standard device support, networking video architecture, video designs, mouse and keyboard support

6. Device drivers, bus drivers, device handles, JDK serial port example

7. Memory, addressing, virtual addresses, page faults, memory regions

8. Interrupts, source tree, IST constructions, registering IS, interrupt dispatch

9. Microkernal, supervisor mode, architecture of interfaces and managers, interrupt processing

10. Booting Java OS boot interface

11. Using introspection to list available methods

12. Design of a command-line interface

13. Adding a process monitor to the JAVA OS

14. System commands for managing threads in JAVA OS

Attendance Policy: Students are responsible to acquire notes and homework assignment from classmates in case of absence.

Weighted

Grading:

Midterm 1/3

Final Examination 1/3

Homework 1/3 includes tests, quizzes, projects, etc.

6. Eng. Applications of Numerical Methods

Eng. Applications of Numerical Methods

Fairfield University

School of Engineering

Course Name & Number: Eng. Applications of Numerical Methods CE ???

Instructor: Prof. D. Lyon

Home Phone:

Business Phone:

E-mail: lyon@DocJava.com

FAX: (203)877-4187

Instructor Assistance: (additional support prior to and/or after class)

Lecture Hours: 3 hours per week starting at 6:30PM

Lab Hours: 0 hours per semester

Course Description:

Root-finding, interpolation, linear algebraic systems, numerical integration, and numerical solution of ordinary and partial differential equations. Substantial programming projects required. The theoretical basis is provided for the students to proceed in computer graphics and voice and signal processing.

PreReq: CE Data Structures in Java, MA 227 (calc III)

Learning Objectives:

After the student take this course, they will know how to write programs that find Roots of Equations using a variety of methods, including Bisection, Newton Raphson, Secant Method and Regular Falsi.

They will also have a basic understanding of the solving of simultaneous equations using Gaussian Elimination, Gauss-Jordan Elimination, LU Decomposition, Jacobi Iteration and Gauss-Siedel Iteration. Students make use of data structures,

and there math background to set up and display solutions Using linear, Cubic & quadratic splines. Students will learn Numerical differentiation and Numerical Integration. Students are introduced to transform methods.

This course requires substantial programming effort and emphasis is place on good software engineering practices.

Outcomes:

1. The students will learn the principles of Numerical Methods.

Expected learning outcomes:

a. Numeric Integration (Trapezoidal, Simpson's, Romberg, Gauss-Legendre)

b. Differential Equations (Euler's Method, Runge-Kutta, Predictor-Corrector)

c. Curve Fitting (least-square lines, splines, Trigonometric Polynomial). Transform Methods (convolution, DFT, DHT, DCT)

2. The student will become proficient with the usage of the Java language.

Expected learning outcomes:

a. Demonstrates the ability to utilize Java in practical numerical method problems.

b. Uses appropriate object-oriented design patterns to solve problems.

After students take this course, they will know how to write programs that can solve problems that have no closed-form solutions. Finally, the students will make use of data structures, linear algebra, and object-oriented design patterns in order to solve numeric methods.

This course requires substantial programming effort and emphasis is place on good software engineering practices.

Outcomes:

When the course is done, Students will have deployed Java applications of their own design, on the web.

Performance Indicators:

Aside from the basics assessment procedures based on homeworks and tests, Students must obtain 75% or better on all tests. Additionally, students must perform at least 75% on the homeworks.

Textbook: Numerical Methods in Java, a manuscript by D. Lyon

Reference Material: Numerical Recipes in C, Press et Al.

Course Requirements:

All homework is to be submitted on time.

The course includes three reporting periods (exam, quiz, project, etc.) and a comprehensive final.

Topics :

1.: Root-finding;

Bisection, Newton Raphson, Secant Method and Regular Falsi.

2. Simultaneous equations using:

Gaussian Elimination, Gauss-Jordan Elimination, LU Decomposition, Jacobi Iteration and Gauss-Siedel Iteration.

3. Approximation

linear, Cubic & quadratic splines. Least-square lines, splines, Trigonometric Polynomial.

4. Numerical differentiation:

Euler's Method, Runge-Kutta, Predictor-Corrector

5. Numerical Integration:

Trapezoidal, Simpson's, Romberg, Gauss-Legendre

6. Transform Methods

c. Transform Methods (convolution, DFT, DHT, DCT)

Attendance Policy: Students are responsible to acquire notes and homework assignment from classmates in case of absence.

Weighted

Grading:

Midterm 1/3

Final Examination 1/3

Homework 1/3 includes tests, quizzes, projects, etc.

7. Computer Graphics

Fairfield University

School of Engineering

Course Name & Number: Computer Graphics CE ???

Instructor:

Home Phone:

Business Phone: SAMPLE

E-mail:

FAX:

Instructor Assistance: (additional support prior to and/or after class)

Lecture Hours: 3 hours per week starting at 6:30PM

Lab Hours: 3 hours per semester

Course Description:

A unified, introductory treatment to two-dimensional and three-dimensional computer graphics concepts. Topics include Human-computer interfaces using the AWT, applied geometry; homogeneous coordinate transforms; Bezier curves, Bernstien Basis Polynomials, Hermite Polynomials, B-Spline curve fitting. Rendering topics: z-buffer algorithm, painters algorithm, raytracing, and texture mapping.

Prerequisite – CE Eng. Applications of Num. Methods, MA 211

Course Objectives and Learning Outcomes:

This course designed to support the visualization and computer systems domain in the CE BS degree.

1. The students will learn the principles of Computer Graphics.

Expected learning outcomes:

a. Applies transform concepts in programming situations

b. Recognizes interrelationships among geometric modeling and computer graphics

2. The student will become proficient with the usage of the Java language.

Expected learning outcomes:

a. Demonstrates the ability to utilize Java in practical visualization problems.

b. Uses appropriate object-oriented design patters to solve problems.

After the student take this course, they will know how to write programs that display and manipulate 3D objects. They will also have a basic understanding of geometric modeling and computational geometry. Finally, the students will make use of data structures, linear algebra, design patterns and basic software engineering.

This course requires substantial programming effort and emphasis is place on good software engineering practices.

Outcomes:

When the course is done, Students will have deployed Java applications of their own design, on the web.

Performance Indicators:

Aside from the basics assessment procedures based on homeworks and tests, Students must obtain 75% or better on all tests. Additionally, students must perform at least 75% on the homeworks.

Textbook: Computer Graphics for Java Programmers by Ammeraal

Reference Material: The Java 3D API Specification

Course Requirements:

All homework is to be submitted on time.

The course includes three reporting periods (exam, quiz, project, etc.) and a comprehensive final.

Obtain data during laboratory hands on session.

Topics (listed by week):

1. Historical perspective and some fundamental issues in hardware, software and applications.

2. The use and implementation of Java 2D, a simple 2D graphics package.

3. Graphics hardware.

4. Transforms in the plane and 3-space, representation by matrices, homogeneous coordinates, 3D views.

5. Java 3D, a 3D floating-point hierarchical graphics package.

6. Human color-vision system, various color-description systems.

7. Shaded graphics, aliasing

8. Visible-surface determination.

9. Illumination and shading, texture, shadows, transparency, reflections,

10. Image manipulations, scaling, shearing, rotation pixmaps. Image storage techniques.

11. Computer Animation.

12. physically based illumination models, .

13. ray tracing

14. radiosity

Attendance Policy: Students are responsible to acquire notes and homework assignment from classmates in case of absence.

Weighted

Grading:

Midterm 1/3

Final Examination 1/3

Homework 1/3 includes tests, quizzes, projects, etc.

8. Voice and Signal Processing

Fairfield University

School of Engineering

Course Name & Number: Voice and Signal Processing CE ???

Instructor: Prof. D. Lyon

Home Phone:

Business Phone:

E-mail: lyon@docjava.com

FAX: (203)877-4187

Instructor Assistance: (additional support prior to and/or after class)

Lecture Hours: 3 hours per week starting at 6:30PM

Lab Hours: 0 hours per semester

Course Description:

Overview of Digital Audio and its application Current state of streaming Audio on the Internet Digital Audio Processing Fundamentals. This course applies the theories laid down in CE Eng. Applications of Num. Methods to the areas of audio processing.

Students will apply the theories of Sampling, Spectra, Fast Fourier Transform Class, convolution and frequency space processing, compression and one-dimensional streaming.

Students will apply the theories by creating programs that read processing and write audio streams. They are exposed to the elements of multi-media network delivery of data. They learn about a wide class of FFT algorithms and elementary sound synthesis.

This course requires substantial programming effort and emphasis is place on good software engineering practices.

Students will learn enough signal processing to take Image Processing, the follow-on course.

Prerequisite – CE Numeric Methods, MA 211 (matrix theory)

Learning Objectives for Voice and Signal Processing

This course designed to support the signal processing and computer systems domain

in the CE BS degree.

When the course is done, Students will have deployed

Java applications of their

own design, on the web. These applications will

demonstrate the usage of Java for real-time

voice and sound processing.

1. The students will learn the principles of Digital Signal Processing.

Expected learning outcomes:

a. Applies transform concepts in programming situations

b. Recognizes interrelationships among signals and spectra

2. The student will become proficient with the usage of the Java language.

Expected learning outcomes:

a. Demonstrates the ability to utilize Java in practical signal processing problems.

b. Uses appropriate object-oriented design patters to solve problems.

After the student take this course, they will know how to write programs that display and manipulate 1D waveforms. They will also have a basic understanding of constructive and destructive synthesis. Finally, the students will make use of data structures, linear algebra, design patterns and basic software engineering.

This course requires substantial programming effort and emphasis is place on good software engineering practices.

Outcomes:

When the course is done, Students will have deployed Java applications of their own design, on the web.

Performance Indicators:

Aside from the basics assessment procedures based on homeworks and tests, Students must obtain 75% or better on all tests. Additionally, students must perform at least 75% on the homeworks.

Textbook: Java Digital Signal Processing by Douglas Lyon

Reference Material: Digital Audio with Java, by Lindley

Course Requirements:

All homework is to be submitted on time.

The course includes three reporting periods (exam, quiz, project, etc.) and a comprehensive final.

Topics :

1. Overview of Digital Audio and its application

Current state of streaming Audio on the Internet

Problems and solutions

2. Digital Audio Processing Fundamentals

Sampling

Spectra

3. The AudioFrame Class

internal data structures

the AudioStream

the AudioDataStream

doubleData

ulawData

the AudioPlayer

building the menu

intercepting menu event

intercepting keyboard events

4. Audio Files

Audio file formats

u-law companding in the Sun AU files

decoding u-law

encoding u-law

reading

writing

playing

graphing

5. Wave Table Generation

Sine

Triangle

Square

Sawtooth

6. Audio Processing

Delay, echo vs. reverb

The Discrete Fourier Transform

The Inverse DFT

The Fast Fourier Transform Class

The Inverse FFT method

Fast Convolution using the FFT

Power Spectral Estimation

Frequency shifting using the FFT

Filtering using FFT

7. Sound Synthesis

Additive Synthesis

Subtractive Synthesis

8. Generalized Modulations

9. Object Oriented Design Patterns and signal Processing

Producer consumer

References

10. Wavelets in Computer Graphics11. Transform compression techniques

12. Multi-media application

13. Telephony

14. Streaming Audio

Attendance Policy: Students are responsible to acquire notes and homework assignment from classmates in case of absence.

Weighted

Grading:

Midterm 1/3

Final Examination 1/3

Homework 1/3 includes tests, quizzes, projects, etc.

9. Image Processing

Fairfield University

School of Engineering

Course Name & Number: Image Processing CE ???

Instructor: Prof. D. Lyon

Home Phone:

Business Phone:

E-mail: lyon@DocJava.com

FAX: (203)877-4187

Instructor Assistance: (additional support prior to and/or after class)

Lecture Hours: 3 hours per week starting at 6:30PM

Lab Hours: 0 hours per semester

Course Description:

A first course in Image Processing; Image algebra,arithmetic operations,boolean operations, matrix operations

Achromatic and Colored Light

Selecting Intensities, Gamma Correction

Chromatic Color, psychophysics, Color models

Color Space Conversion, low-level pattern recognition.

Students will learn the theory of 2-D Fast Fourier Transform Class, 2D convolution and frequency space processing, compression and 2D streaming.

Students will apply the theory by creating programs that read processing and write image streams. They are exposed to the elements of multi-resolution multi-media network streaming. They learn about a wide class of transforms, including Wavelets, DCT, the PFA FFT and others.

This course requires substantial programming effort and emphasis is place on good software engineering practices.

Students will learn enough signal processing to write their image processing applications.

Prerequisite – PreReq: CE Voice and Signal Processing

Learning Objectives for Image Processing

This course designed to support the signal processing and computer systems domain in the CE BS degree.

When the course is done, Students will have deployed Java applications of their own design, on the web. These applications will demonstrate the usage of Java for image processing.

1. The students will learn the principles of Image Processing.

Expected learning outcomes:

a. Applies transform concepts in programming situations

b. Recognizes interrelationships among signals and spectra

2. The student will become proficient with the usage of the Java language.

Expected learning outcomes:

a. Demonstrates the ability to utilize Java in practical image processing problems.

b. Uses appropriate object-oriented design patters to solve problems.

After the student take this course, they will know how to write programs that display and manipulate 2D images. They will also have a basic understanding of image filtering. Finally, the students will make use of data structures, linear algebra, design patterns, voice and 1D signal processing.

This course requires substantial programming effort and emphasis is place on good software engineering practices.

Outcomes:

When the course is done, Students will have deployed Java applications of their own design, on the web.

Performance Indicators:

Aside from the basics assessment procedures based on homeworks and tests, Students must obtain 75% or better on all tests. Additionally, students must perform at least 75% on the homeworks.

Textbook: Image Processing, in Java by Douglas Lyon

Reference Material: Java Digital Signal Processing, By Dougas Lyon

Course Requirements:

All homework is to be submitted on time.

The course includes three reporting periods (exam, quiz, project, etc.) and a comprehensive final.

Topics :

Topics: (coverage will be altered to encompass the latest APIs)

Week 1: Using the AWT - The new Event model

The Graphics Class

Test Patterns

Color Bars

resolution chart

multi-burst test chart

Snell and Wilcox test chart

Interaction

The mouse

The keyboard

The Evt class

building the menu

intercepting menu event

intercepting keyboard events

Week 2: The Model-View Approach

observables and the dialogs boxes

Int Dialog

Float Dialog

File dialogs

The ImageFrame Class

oldPixels

newPixels

menu construction

Week 3: Streams

File input stream

stream tokenizer

closing a file

token flags

writing files

summary for writing files

Save File Example/ set-up main menu bar

Process menu pick - save

Week 4: Digital Image Processing Fundamentals

Overview of Image Processing and its application

Image Storage and Display

image models

cameras video and scanners

Current state of streaming video on the Internet

Problems and solutions

Sampling

Spectra and Spectra

Preview of Image processing

Week 5: The PixelPlane Class

range checking

PixelGrabbers

internal data structures

the ImageStream

the ImageDataStream

Image doubleData

Reading and Writing Images

Reading GIF and JPEG

Writing GIF

Reading PPM

Writing PPM

Week 6: Edge Detection

Roberts, Prewitt, Frei-Chen,

Kirsch, Sobel,

boxcar, pyramid, argyle, Macleod,

derivative of Gaussian, Robinson,

Canny

Laplacian generation, Laplacian of Gaussian

Hat

Week 7: Boundary Processing

XY to Vector Conversion

vector ordering using Dijkstras' algorithm

Edge following and Martellis' algorithm

Divide-and-conquer boundary detection

Range finding via diffraction

Range map to boundary representation

Week 8: Image Enhancement Techniques

Blur

mean, median, unsharp

smoothing binary images by association

local area contrast enhancement

histogram equalization

lowpass filtering

highpass filtering

averaging multiple images

Week 9: Achromatic and Colored Light

Selecting Intensities-Gamma Correction in Java

Chromatic Color

psychophysics

Color models (CIE, RGB, YUV, CMY, HSV, YIQ)

Color coordinate systems

RGB to L*u*v*, L*u*v* to RGB

RGB to L*a*b*, L*a*b* to RGB

RGB to XYZ, XYZ to RGB

RGB to YIQ, YIQ to RGB

RGB to YUV, YUV to RGB

RGB to HSV, HSV to RGB

RGB to HLS, HLS to RGB

Week 10: Thresholding techniques

Global thresholding

multilevel thresholding

variable thresholding

thresholding using image statistics

using mean and standard deviation

using maximization of between-class variance

Week 11: Morphological filtering

set theory

arithmetic operations

boolean operations

erosion and dilation

medial axis transform

skeletonization

Week 12: Warping

scaling

rotation

shear

cutting and pasting

conformal image mapping

warping

Week 13: The Cosine Transform

The Discrete Cosine Transform

The Inverse Discrete Cosine Transform

The Fast Cosine Transform Class

Reading and Writing JPEG Images

Week 14: The InLine MPEG CODEC

Compressed MPEG movies images

decoding MPEG

encoding MPEG

reading MPEG files

writing MPEG files

displaying MPEG files

measuring loss

Implementing in-line Java Decoders

Week 15: The Wavelet Transform

The Discrete Wavelet Transform

The Inverse Discrete Wavelet Transform

The Fast Wavelet Transform Class

Writing a wavelet encoded file

Decoding the wavelet encoded file

Incorporating the decoder with the data

Distribution of wavelet images on the Net.

Attendance Policy: Students are responsible to acquire notes and homework assignment from classmates in case of absence.

Weighted

Grading:

Midterm 1/3

Final Examination 1/3

Homework 1/3 includes tests, quizzes, projects, etc.

1. DATA Structures in JAVA

PreReq: CS131

Performance Indicators:

2. Digital Design I

Basic digital design principles. Boolean algebra. Combinational logic design with gates, MSI, LSI. Sequential logic design; register, counters, memory and PLD. PreReq: EE 213

Performance Indicators:

3. Digital Design II

Computer architecture implemented using a hardware design language and PLDs. Students design, implement and program small RISC machines.

PreReq: EE 245

Performance Indicators:

4. Computer Networks

Performance Indicators:

5. Operating Systems in Java

PreReq: Data Structures in Java

Performance Indicators:

6. Eng. Applications of Numerical Methods

PreReq: CE Data Structures in Java, MA 227 (calc III)

Performance Indicators:

7. Computer Graphics

Performance Indicators:

8. Voice and Signal Processing

Performance Indicators:

9. Image Processing

Prerequisite – PreReq: CE Voice and Signal Processing

Performance Indicators:

Basic digital design principles. Boolean algebra. Combinational logic design with gates, MSI, LSI. Sequential logic design; register, counters, memory and PLD.
PreReq: EE 213