I wrote an explainer on classic edge detection algorithms (Sobel, Canny, Laplacian) while building an interactive tool that lets you upload an image and compare their outputs side by side.
The post focuses on:
- What each algorithm is actually doing under the hood
- Where each one works well (and where it doesn’t)
- Why Canny feels “better” in many cases but costs more compute
- Practical tradeoffs rather than just theory
The tool runs entirely client-side, so no images are uploaded to a server.
Would love feedback from folks who’ve used these algorithms in production or teaching.
The post focuses on:
- What each algorithm is actually doing under the hood
- Where each one works well (and where it doesn’t)
- Why Canny feels “better” in many cases but costs more compute
- Practical tradeoffs rather than just theory
The tool runs entirely client-side, so no images are uploaded to a server.
Would love feedback from folks who’ve used these algorithms in production or teaching.