1. Course Components Lateness penalty - 20% per half week, with special rules at end of semester, and for special cases applicable to all students in the class. Grading count best: 10 homeworks, 5 projects and 3 presentations Revised 000223

2. Project #1 -- Choose one PJ1A: Demonstrate the degradation of an image with repeat scan-print cycles. Minimize degradation where possible (due 2/2) PJ1B: Improve the performance of a color printer using PSP or Photoshop adjustments, and testpict.tif. Project applicable only if the result is an improvement. (due 2/9)

3. Alternate 3 for Project 1 PJ1C: Give the idea behind LUT and PSP. –Due 2/9

4. MiniProject #2 for 2/16 PJ2A: Do a recap on how best to accomplish the steps in Figure 3-25 using PSP or other available image processor. Give specifics.

5. Alternate MiniProject #2 for 2/16 PJ2B: Do a recap on the rolling ball and top hat filters -- with particular emphasis on explaining pages 188-189 in text.

6. MiniProject #3 for 3/1 PJ3A: Program a macro for Scion that will automate a particular processing function on an image. (For further discussion, as to what processing function is to be automated.)

7. More on Scion Macros Scion Image can be extended using a Pascal-like macro programming language that allows users to customize and automate repetitive and frequent tasks. The easiest way to develop a custom macro is to modify one of the macros in the Macros folder distributed with Scion Image. Macros are stored in text files that can be edited using Scion Image’s built-in text editor. Using the Load Macros command causes the macros in the file to appear as commands at the bottom of the Special menu. The macro language is described in Appendix A. The description assumes some familiarity with the Pascal programming language. Additional help on macro writing, and other ways to extend Scion Image, can be found in a separate document named “Inside Scion Image “.

8. Alt MiniProject#2 for 3/1 PJ3B: Design a filter scheme to remove flash glare from images. Consider background removal, cloning, and dodging, as well as design of your own linear filter. Describe the advantages/disadvantages of each and show the best before/after comparison.

9. Idea for MiniProject #3 for 3/1 PJ3C: Setup an arrangement so that Matlab can provide an isometric plot of a BMP image that has been processed using one of the other image processing packages.

10. Miniproject for 0308 How could we locate rice grains independent of orientation? This is an open ended question with which there is some level of difficulty and for which there could be many approaches. Consider the use of correlation among the choices. PJ4A

11. Alternate for 3/8 PJ4B: Pick 3 filters/processors not discussed yet in class. Add to the table processors.doc Provide an illustration of their function using a ‘manufactured’ or real image, or better yet, both.

12. Villi ‘grains’ PJ5A The villi contain some small dark grains. Process the image to improve the view of the grains. Investigate what measurement details may be extracted from the grains, using IT. (This is open-ended, so please try innovative approaches where possible.)

13. Automated Bugs A proposal has been made to develop an automated image analysis system for inspecting bugs. You are asked to develop such a system. The initial assumptions for development are: 1. This is always one and only one bug in each image. 2. The bugs are always aligned in a standard position. 3. The bug antennae are thinner than bug legs. When feasible, the system is to be broadened to analysis of images for which these assumptions are not valid. Measurements to determine for each bug are: Overall bug size Number of legs Length of each leg Number of antennae Length of each antenna Consider pre-processing, segmentation, and analysis.