AP 186 Activity 13: Color Image Segmentation

I've been meaning to use a picture of my brother Miguel for a long time, just for fun. In this activity, I finally did. I like this picture of him because he's annoyed and laughing at the same time, plus it's quite perfect for image segmentation because a number of colors in the image really stand out. For this activity, let's focus on the corn he's holding. This was taken using my cellphone camera, at 2MP. I love you dear K770i.

Fig 1. My brother Miguel.

Let's have an overview first of the two segmentation techniques we'll be using in this activity. First is Parametric Segmentation; it's basically getting a region of interest (ROI) in the image then transform its color RGB into normalized chromaticity coordinates using the equation below:

Then the probability function of r and g is solved to test the likelihood that a pixel belongs to the ROI. We used the Gaussian function to compute these probabilities.

As for Non-Parametric Segmentation, the 2d histogram of the image was taken and then using this we back project to segment the image. The results are below:

Fig 2. Parametric (left) and Non-Parametric (right) segmentation.

I observed that Parametrically segmented images are cleaner, and the matching parts in the image with regards to the ROI really shine. On the other hand, Non-Parametrically segmented images have a lot of noise and unwanted data. However since I used a colorful picture, and colors all have red, green and blue, the Non-Parametric method was more sensitive to the presence of the hues in the ROI that were present in the image itself.

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AP 186 handout

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I give myself 10 for this activity because I think I understood well the concept of these two techniques of color segmentation, plus I got to use a picture of my brother.