BOWIE STATE UNIVERSITY
Department of Computer Science
Course Syllabus
COURSE NO: COSC 719(3 cr.), TITLE: Image Processing I SEMESTER: Fall 2011
ROOM: CSB314, TIME: Tues 4:55 PM - 7:25 PM
Instructor :
Office :
Office Hrs :
Telephone :
email :
Manohar Mareboyana
CSB 221
Tuesday 2:30 p.m. - 4:30 p.m.
(301) 860-3971
mmareboyana@bowiestate.edu
Catalog Description: This course is an introduction to Computer Vision and Image
Processing fundamentals, human visual system, image resolution, binary images, gray
scale images, multispectral images, digital image formats, preprocessing, image algebra,
spatial filters, image enhancement, edge detection, segmentation, feature extraction
etc. Additional topics include discrete transforms and image compression techniques.
POLICIES REGARDING ATTENDANCE, GRADING, HOMEWORK AND
ACADEMIC INTEGRITY
Evaluation: Following is the Evaluation system for the Final Grade. Each homework
will be graded. Students are responsible for completing them as scheduled.
Homework/Assignments:
Projects:
Quizzes:
Mid-Term Exam:
Final Exam:
10%
20%
20%
20%
30%
Projects, Mid-term and Final exams are mandatory. Mid-term will not include the grades
of projects.
Grading: Academic dishonesty will result in grade F. The grade levels used in
evaluating students’ work are:
90 - 100 A
80 - 89 B
70 - 79 C
Final grades will be computed based upon credits earned for all the five components
mentioned above.
Attendance: Regular attendance in the class is mandatory. Students will be responsible
for any loss of information, assignments, and projects due to absence from class.
There will be no make-up for any missed classes, projects, assignments, and exams.
Help: During the office hours or by appointment. Email can be used for help but I check
emails prior to schedule class meeting. Please use the homework email to email
me. The reply may take more than 24 hours. While sending email, always mention
your name and a proper subject that reflects the problem in brief. Always use
teacher’s email address given in this syllabus. The instructor will check emails from
students only at this address. Also, due to virus problems, student should use only that
address that is given to the teacher in Student Information Sheet by the student. If you
send from some other address, it might go to junk area and you may not get a
response.
Academic Dishonesty: Academic dishonesty includes plagiarism, cheating, and
other illegal or unethical behaviors in doing the work of the course. Plagiarism is
the act of representing another's ideas, words or information as one's own. If you
receive assistance on an assignment from someone else, you must avoid
plagiarism by giving proper credit for this assistance. Include in your assignment
a comment naming the person who assisted you and stating what the assistance
was. Students who are guilty of academic dishonesty are subject to severe
penalties ranging from a reduction in points (and possible failure) for the
assignment/project, to failing the course, or in extreme cases, dismissal from the
University. Do not copy other student's projects, codes, and design. A group of
students working together on a project must change their forms and codes to
differentiate from others.
Inclement weather conditions: In case of inclement weather conditions, call the
following number regarding cancellations: (301) 860 - 4000.
Important Numbers:
Dept of Comp Sc (Secretary): (301) 860-3961
Dept of Comp Sc (Fax): (301) 860-3979
Blackboard Information:
Website: http://classroom.bowiestate.edu
Help Desk: (301) 860-4357
It will be the student's responsibility to logon and be comfortable with the use of
Blackboard established for them. Call the help desk if there is any problem in accessing
the Blackboard. Also, be comfortable with zipping the files as students are required to
submit all the zipped Project files on Blackboard using digital drop box.
ADA statement: Students with disabilities who wish to receive ADA accommodations
should report to the Office of Special Populations, CLT Building Room 311 (telephone
301-860-3292)
The Important Dates
Late Registration:
Last day to add a Class:
Last Day to drop without a W:
Convocation:
Last Day to change from Credit to Audit
Last day of Classes:
Final Exams:
TBA
TBA
TBA
TBA
TBA
TBA
TBA
Required text:
Digital Image Processing, Rafael C. Gonzalez and Richard, E. Woods, Third Edition,
Prentice Hall,
ISBN: 0-13-168728-x
Teaching Modes:
The primary teaching mode will be lecture-discussion, problem solving. This will be
supplemented by out of class conferences, discussions.
Course Objectives: Upon successful completion of the course, the students will be able
to:
1. demonstrate the image concept as a mathematical function
2. demonstrate use of various operators on image functions
3. demonstrate and implement some common image enhancement and feature
detection methods.
4. demonstrate knowledge of color images, multi-spectral image formats, storage
and processing.
5. develop a project on image processing project using OpenCV, Matlab
REQUIREMENTS: Students are expected to:
1. Attend all classes, participate in class discussion, and otherwise be prepared.
2. Read all assigned selections before coming to class on the day those selections are
to be discussed.
3. Submit all assignments when due (1/2 letter grade off for each day late without
documented excuse; papers more than one week late will not be accepted.)
4. Implement projects using the software provided.
COURSE OUTLINE & SCHEDULE: (schedule subject to change with due notice)
There will be daily homework assignments administered during class.
Week
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Topic
Theoretical foundations of image representation
Mathematical operators applicable for digital images
Image digitization, sampling and quantization
Image smoothing and noise filtering techniques
Image Enhancement and contrast improvement
Image segmentation and feature detection
Mid-term exam
Image transforms: Fourier transform, Haar Transform and Wavelet
Transforms
Introduction to Matlab, openCV and development of simple image
processing projects
Color images and multi-spectral images
Image Compression techniques and standard image formats, Compression
ratio, Signal to noise ration
JPEG, Wavelet compression techniques
Vector Quantization and its variations
Review for the final Exam
Final Exam
Bibliography:
1. Computer Imaging: Digital Image Analysis and Processing by Scott E Umbaugh,
CRC Press, 2005, ISBN: 0849329191
2. Kenneth R. Castleman, Digital Image Processing, Prentice Hall 1979.
3. A. K. Jain, Fundamentals of Digital Image Processing, Prentice Hall1,1989.
4. J. D. Gibson, T.Berger, T. Lookabaugh, D.Lindbergh and R. L. Baker, Digital
Compression for Multimedia principles and Standards, Morgan Kaufmann,1998.
5. Gonzalez, Woods, and Eddins, Digital Image Processing Using MATLAB ,
Prentice Hall, 2004.
6. Gregory A. Baxes, Digital Image Processing: Principles and Applications,
Wiley, 1994.
7. Michael Seul, Lawrence O'Gorman, Michael J. Sammon, Practical Algorithms for
Image Analysis: Descriptions, Examples, and Code, Cambridge University Press,
2000.
8. IEEE Transactions on Image Processing (Periodicals from IEEE press)