Rensselaer
Polytechnic Institute
ECSE
35-6640 Digital Picture Processing - Spring
2005
Monday-Thursday
First
meeting on January 24
Instructor:
Professor George Nagy (
Office hours:
Tuesday and Wednesday
Prerequisites:
programming skills; linear systems and data structures
desirable
Grading:
5 programming assignments
50%
5 non-programming assignments
20%
Term paper
10%
Software trial by fire
20%
Text:
O’Gorman, Practical Image Processing Algorithms??
Topics:
Image acquisition and
display
Spatial
sampling and quantization: scanner test charts and
calibration
Common
image formats, representation, and compression methods
Image and
text compression methods and software
Elementary
picture-processing operations; morphology
Geometric
and intensity quantization and normalization
Picture
segmentation and connected component labeling (CC)
Image
registration (2-D and 3-D)
Vectorization
and tracing as an alternative to thinning and
skeletonization
Color
models, formats, and transformations
Digital
watermarking andsteganography
Image
databases and digital libraries
Selected
applications: documents, biomedical, biometric, remote
sensing
Programming
assignments:
P1. Binarization methods
P2.
Connected components
P3.
Morphological and convolution operators
P4. Object
location and segmentation
P5. Vectorization
Non-programming
Assignments:
NP1 Analysis of a
scanned test chart.
NP2 Compression
NP3 X-Y trees
Term paper
NP4 Transformations
in color space
NP5 Image
warping
Course objective:
All of the programming
assignments will be based on a file of optically scanned documents, which we
will use to demonstrate various picture processing algorithms. On completion of the course, students
should be sufficiently familiar with the (meager) theoretical foundation,
notation and vocabulary of digital picture processing to pursue matters of
interest in the current technical literature. They will understand some of the
engineering aspects of a prototypical application of digital picture processing