Kristine Faith Roque's AP 186

In this activity, we will explore different image types and file formats. There are four basic image types: binary, grayscale, truecolor, and indexed images. Here are some examples of each type together with their information. Note: imfinfo outputs the following image information-> File Name, File size (bytes), Width, Height, bit depth, and Color type 1. Binary image Image taken from:  http://upload.wikimedia.org/wikipedia/en/3/33/Neighborhood_watch_bw.png The extracted image information using Scilab imfinfo are: (The bit depth is 8 because imfinfo in SVIP module only outputs either grayscale or true color and represents the 1’s and 0’s of a binary image with 255 and 0 as shown below.) 2. Grayscale image Image taken from:  http://www.codeproject.com/KB/GDI-plus/ImageProcessing2/grayscale.jpg Image information: 3. Truecolor images Image taken from:  http://media.smashingmagazine.com/wp-content/uploads/2010/05/PaperArt98.jpg Image in

For the second activity we had a bit of practice in using the SciLab programming language. We had to produce the following synthetic images: a.        Centered square aperture b.       Sine wave along x direction (corrugated roof) c.        Grating along x direction d.       Annulus e.       Circular aperture with graded transparency (Gaussian function) But first we had to follow a sample code given by Dr. Soriano. The code produced a 100 x 100 pixel – image of a centered circular aperture with radius of 35 pixels (Figure 1). Figure 1. Code and synthetic image for centered circular aperture After doing the centered circular aperture I am ready to do the other synthetic images. The easiest was the annulus since you just have to tweak the code for the centered circular aperture. I just replaced line 7 of the code with: A(find(r<0.7 & r>0.3)) = 1. This logical statement would only return True for regions between circles with r<0.7 and r>0.3, hen

The first activity for our AP 186 class was very interesting and quite useful. I have had problems before concerning manufacturers who give calibration curves but do not give the values. It’s really troublesome when you need them and you can’t find any way to retrieve the data. Fortunately, this digital scanning experiment resolves this dilemma. Way back when computers were not yet easily accessible, graphs were still hand-drawn. In this activity, we went to the CS Library to find old journals or thesis papers from which we can choose a hand-drawn graph. Our chosen graphs are to be scanned as an image where data are to be extracted. The graph that I chose was taken from the PhD Dissertation of Cherrie B. Pascual in 1987, titled, Voltammetry of some biologically significant organometallic compounds . The scanned image was tilted so I had to rotate it using Gimp v.2 (see Figure 1). Figure 1. Concentration dependence of DPASV stripping peaks of triphenyltin acacetate usi