Introduction to Image Processing Our first look at image processing will be through the use of Paint Shop Pro, a bitmap editing program available as shareware. Notice: After 30 days you must purchase a registered copy of Paint Shop Pro from JASC or you must uninstall it from your computer. This program is an excellent addition to your software tools. Please encourage the development of high quality software by registering all shareware programs that you find useful. (Sermon ends.) Paint Shop Pro has an option for User-Defined filters that we will use to demonstrate a number of image processing techniques. The user-defined filters are created in the form of a template that holds weights for a Sigma-Pi filter (i.e. a filter that multiplies a number of adjacent pixels by some value and then sums them to compute a new value for each pixel). a pixel in the image template containing weights

Lets play with the templates before we try to understand them mathematically. 1. Create a simple black and white image. 2. Build the Laplacian template as shown below. 3. Apply the Laplacian to your image.

Image Processing Algorithm Development Assignment: In this assignment you will develop (and possibly implement) an image processing algorithm. A simple binary image is shown below that contains different shapes of solid objects. We are interested in the 26 pixel diameter circles in the image. Your task is to develop an algorithm that detects the 26 pixel diameter circles and lists them (i.e. outputs a list of the centers of these circles) If you are a CS major, it is preferred that you build a program that accepts the image file and outputs the list of centers. If you do not have a programming background you can implement some of the signal processing steps in Paint Shop Pro and give a written description of the rest of your algorithm (i.e. pseudocode).

Your algorithm should be able to operate with reasonable performance on images with overlapping objects as shown in the examples below: The original image and these two images as well as a sample Ada program to read raw image files are available in the CSC 508 Web page. imgpro1.bmp rawimagereader.adb imgpro2.bmp imgpro3.bmp In order to use the rawimagereader.adb program you will need to convert the.bmp files to.raw using Paint Shop Pro or a similar package. Paint Shop Pro 3.11 is available on my Web Page (see CSC 299).

OK, Where Do I Start? Step 1: Don't Panic. Step 2: First think about how you would work this problem by hand (actually by eye). Let's list a few pertinent questions for solving this problem. a. How can you find out where the objects (black blobs of pixels) are in the image? b. How can you tell circles from rectangles? c. How can you determine the diameter of a circle (in pixels) in the image? d. How can you find the center of a circle (in terms of x,y pixel values)? Step 3: Consider any preprocessing that might make the problem easier. Preprocessing is anything you do before detection. In this example, detection is finding the objects. Step 4: Write down in detail what you are doing when you find a 26 bit diameter circle by eye. Step 5: Try to rewrite the description in step four in terms that could be converted to source code. Step 6-???: Implement your pseudocode.

Still Confused? Bring up imgpro1.bmp in Paint Shop Pro, increase its colors to 16 million and begin to apply the Dilate filter (this is one of the special filters listed under the Image command. As you repeatedly apply this filter notice what is happening to the black objects. (If the objects were white against a black background you could use the Erode filter instead.) Now try the Dilate filter on imgpro2.bmp and imgpro3.bmp. You might also consider building and applying some user-defined filters such as the Laplacian. The point is, you should play around with the images and the filters, make note of what is working and build your algorithm as a series of filters applications and possibly a pixel- by-pixel search of the modified image. If you're still having trouble, send me .