bundito's profile - activity

Hello again @LBerger and @eshirima ! I successfully ran all my images through a K-Means implementation from the sklearn

@LBerger: I wasn't aware of the device fingerprinting going on. It must be part of the generic WordPress install. I'll f

Hi OpenCV’ers!

I’ve got a project in mind and need some expert input. I have a collection of about 1100 abstract images (desktop wallpaper tiles) that I want to be searchable by predominant color.

I’ve already found Python code to help me use the OpenCV libraries to do k-means clustering and extract the top 3 (for example) colors in each image. From that, I can get the three colors as RGB values and the percentage of each.

I plan to stuff all that data into a database for searching.

Ideally, I want the program user to select a color (using a standard color-picker dialog box), and then query the database for the top X images with the “closest matching” predominant color.

The problem is that I don’t know how to store and search this data effectively. That’s where I need your help. The math involved here is miles over my head.

From doing some reading (Wikipedia), I have a hunch that storing and searching HSV values makes more sense than RGB values. I can’t fully explain why, except that it seems easier to find “more or less blue-ish” using HSV.

Is anyone willing to help me untangle this? I thought this project would be straightforward, until I started digging into image analysis. This led me to k-means clustering, which led me here.

Thanks in advance.

Can I also use the distance calculation you described to determine the level of "contrast" between the top 3 colors in t

Thank you. It seems you understand what I'm trying to do. My database will be SQLite, so I can easily pack the database

Find an image by nearest color? Hi OpenCV’ers! I’ve got a project in mind and need some expert input. I have a collect