CSCI 181 (S '09), Topics in Image Analysis

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Overview
A survey of topics in the acquisition, processing and analysis of digital images, with much of the necessary mathematical background developed in the course.  Topics in image processing include image enhancement and restoration, compression, and registration/alignment.  Topics in image analysis include classification, segmentation, and more generally statistical pattern recognition.  Throughout the course, human vision and perception motivate the techniques discussed.  Requires CSCI 62.

Specific topics to be covered in more or less depth:

• human visual sytem and perception
• filtering and contrast enhancement (windowing, blurring, sharpening, histogram methods)
• segmentation (Canny edges, face detection, Hough transform, Bayesian segmentation formulation)
• registration (transforms, sum of squared-differences, correlation, corner detection, homographies/photo stitching)
• image compression (LZW, Fourier, wavelets)

Is CSCI 181 For You?

1. Although this course requires CSCI 62 or equivalent.
   
2. As an upper level CS elective, it would be helpful in this course to have some calculus and linear algebra (how to take a derivative of a simple function, matrix algebra). 
   
3. Mathematical and statistical entities like probability distribution, histogram, Gaussian, and others will be developed in class insofar as we need them.
4. We will be using MATLAB for all our work.
   

Time Commitment
During the course of CSCI 181, you will work on several thought-intensive projects. This can be a time-consuming process. Expect to spend 10-12 hours on each programming assignment (depending, of course, on the specific assignment). 

Textbooks
Required: Gonzalez, Woods: Digital Image Processing, 3rd Edition (2008) (available through the bookstore or amazon).

Potentially useful:  Richard Szeliski, Computer Vision: Algorithms and Applications.               

1. Given the limited amount of class time and the fact that this course is meant to be compatible with those at Pomona and Harvey Mudd, attendance is very strongly encouraged.
2. Grading breakdown: Exams 40% (2 x 10, 1 x 30),  Assignments 50%, Attendance and Participation 10%.
3. Late Assignments lose 10, 15, 25, 25, 25% for each additional day late (no credit on the fifth day).  This scale may be delayed given the severity of your circumstances and my being informed of them in a timely manner.
• I will defer to the Counseling Center (see http://www.cuc.claremont.edu/counseling).
• If you have an athletic event and will not be able to make a deadline, you should tell me within a day of an assignment being posted.