Blob Coloring and HSRB Proposal 11/11/2017

This week, some interesting things happened. Firstly, our proposal got accepted and we can now move on to the next step of submitting an HSRB proposal. Both Taylor and Myself have taken a hour long online class on how to run a good study, and we are currently working together to finish questions for next year and get the proposal submitted by Tuesday.

The most interesting things however, was our discussion with another computer science professor at our college, that led us in a different direction in edge detection.

Dr. Ferrer

Dr. Ferrer is a professor at our college who has some experience with object detection in his own research. Using a robot that can take pictures, he has headed a project that analyses those images, and allows the robot to respond. As part of his research, he uses something called…

Blob Coloring and K-Means Clustering

20171110_145811
Blob coloring – given a picture is a set of pixels, create a list containing references

Instead of detecting edges, blob detection finds regions of color, and defines them by certain aspects of themselves, namely, their size, how many pixels they have, their aspect ratio, etc. These regions of color, or blobs, are literally themselves with more information. Part of finding them however, is how many blobs you expect to be there to begin with.

20171110_145814

Finding out how many blobs there are depends on how many distinct colors you expect to find in the image. Before you use blob detection, you first need to determine the distinct number of colors in the image, and then cluster these colors together. Both Dr. Ferrer, and our adviser suggested using k-means.

 Instead of rewriting code for this by hand, Dr. Ferrer offered to let us use some of his code, and then re-implement it in respects to our programs functionality.

cluster
Dr. Ferrer’s wonderful clustering program.

Using this blob detection, we should be able to find the fitness of certain aspects of our images. From there, we can work on getting our aesthetic measure done by the end of the semester.

Extra

I managed to hook up Taylor’s code to my code for exporting. Although she doesn’t have randomization, it is set up so she will be able to get it to do so and export automatically!

lsystem saves now

It was brought up that my program should be able to somewhat intelligently pick colors. Unfortunately, this is the progress towards that.

poor color attempt
A color attempt where one of the RGB values will randomly increase/decrease by a set amount, if it gets too low or too high, the color is re-randomized.

 

dumb colors4554
A color attempt at a rainbow gradient, each RGB value gradually shifts. Based on this.

HSRB

Work on HSRB progresses. Taylor is doing the dirty work of filling out forms, and I have been working on fliers. Below are a couple quick mockups.

Research Example1   Research Example2   Research Example3   Research Example4

I also edited the questions associated with the research project and wrote a debriefing for afterwards.

Goal

Our current goal is to have our aesthetic measure done by the end of the semester, and begin our evolution next semester.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google+ photo

You are commenting using your Google+ account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

w

Connecting to %s