Edge detection

25 Sep 2016

I built a basic image edge detector. Each image above represents a different step in the pipeline. First the image was smoothed using cross-correlation with a 5x5 Gaussian kernel, effectively smoothing the image. Edges were then enhanced by computing the gradient magnitudes (root sum of squares of X and Y gradients), applying normalization, and converted to black-and-white with a threshold of 120 intensity.

The application was built in Python, and the original image was taken at the Millenium Park in Chicago.

Due to proprietary, privacy, or academic concerns, the source code is not publicly available, but can be happily provided upon request.

Me

I'm a software engineer, proud veteran, and even prouder husband and father. I live and work in Silicon Valley, and love to learn about learning (EdTech), ML/AI/RL, and cybersecurity.