Image Processing

CSCI 5532 - Fall 2005 Syllabus

Title: Pattern Recognition and Image Processing

Instructor: Dr. David E. Pitts
Faculty Office: Delta 230
Phone:281-283-3350 or 3844
Fax:281-283-3870 or 3869
Webpage: http://sce.uhcl.edu/Pitts/
E-mail:


Office Hours: The Hour prior to each class.

Textbook: Gonzalez, R.CX. & Woods, R.E.., Digital Image Processing
Prentice Hall. 2002. 2nd ed. ISBN 0-201-18075-8.

DESCRIPTION: Software and Hardware techniques for image processing and extracting useful information from images by automatic means.

Objective:To provide the student with a working knowledge of digital image processing techniques for transforming a given image into another image having desirable properties, such as enhancement of particular features.

Methodology:1. Lectures on new concepts.
2. Home work problems for experience and familiarity with methodology.
3. Programming problems on the Sun workstations to demonstrate understanding of, and ability to ultize, image processing techniques.

Prerequisite:Calculus, Linear Algebra, Probability, Statics
and a Compiler Language.

Appraisal:Homework                          5%
Programming Problems    40%
Exams                               30%
Research Paper                20%
Presentation                      5%

Attendance:Students are expected to attend class regularly.

Honesty Code:The Honesty Code is the university community's standard of honesty and is endorsed by all members of the University of Houston-Clear Lake academic community. It is an essential element of the University's academic credibility. It states:

 I will be honest in all my academic activities and will not tolerate dishonesty.

COURSE OUTLINE
Aug 24  Chapter 1, Introduction, uses of image processing Image acquisition, media (film, CCD, TV, DTV), formats overview.
               Targa Format, Template Program. Assign Research Paper.

Aug 31  Chapter 2, Digital Image Fundamentals, Perception, Adaptation, Discrimination, Sampling, Image Fundamentals,
               Connectivity, Distance, Arithmetic, Logic, Assign Homework 1.

Sept 7  Chapter 3, Grey level histograms, gray scale manipulation, thresholding Histogram equalization, Histogram
               Specification, Homework 1 Due! Assign Program 1.

Sept 14  Chapter 3, Spatial Filtering; Gradient Operators Spatial Smoothing, Laplacian, Median, Replacement


Sept 21 Chapter 9, Morphological Operators Program, 1 Due, Assign Program 2


Sept 28 Chapter 9, Morphological

Oct 5  Mid - term exam
             Convolution, section 4.2.4, Convolution with Gaussian


Oct 12  Canny Filter, Dirac Delta Function , Tie Point Registration, translation, scaling, rotation, destriping, resampling,
               Section 5.11. Program 2 due, Assign Program 3


Oct 19 Chapter 4, Fourier Transform
               Review Mid- term exam
               Program 3 Due, Assign program 4
               Paragraph Due describing your topic for the research paper.

Oct 24    Last day to drop

Oct 26    Chapter 4, Filter Design, Homomorphic Filter.

Nov 2    Chapter 5, Image restoration., Inverse, Power Capstrum Filters, Program 4 due


Nov 9    Chapter 6 HSI Space, Color models, Decorrelation Stretch, Color Targa format


Nov 16   Chapter 11,Segmentation, Hotelling Transform - Principal Components Texture Analysis Hough Transforms.


Nov 30   Final Exam

Dec 7    Class Presentations Research Paper Due at 7 pm

GRADING SCALE (%)
Grading:Deductions will be assessed on all late assignments and tests. Starting with the 2nd assignment, deductions will be assessed when students ask the instructor to debug their programs.

      MINUS    NO SIGN    PLUS
A     90-92         93-100

B     80-82         83-86    87-89

C     70-72         73-76    77-79

D     60-62         63-66    67-69

F                       <60   

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