Show HN: My compact, bio inspired distributed edge detection algorithm
Hi HN, I've been working on a bio / visual cortex inspired edge detection algorithm. I released a preliminary version a couple of months ago, and I've been improving it since. Benchmark scores currently sit midway between old-school (Canny, Sobel), and modern deep nets, while having the former's interpretability. I'm planning to develop this further for downstream use cases, maybe try to improve FPS for video and performance on different hardware. For anyone interested in a collaboration you can
Read original source
Source record
Recorded metrics
points · 3 votes
2026-11-09 06:15:25.067Z
cumulative since publication
Research analysis
Project record
Repository: RenderBear/haci. Source account: Hi HN, I've been working on a bio / visual cortex inspired edge detection algorithm. I released a preliminary version a couple of months ago, and I've been improving it since. Benchmark scores currently sit midway between old-school (Canny, Sobel), and modern deep nets, while having the former's interpretability. I'm planning to develop this further for downstream use cases, maybe try to improve FPS for video and performance on different hardware. For anyone interested in a collaboration you can
Observed adoption & comparisons
Source votes: 3 votes (Nov 9, 2026 UTC; cumulative since publication) Recent records to compare: “Show HN: FELF – AppImage-like single binaries without FUSE, root, or a runtime” (Show HN, Nov 8, 2026); “Show HN: After decades, I have my almost perfect music player” (Show HN, Nov 8, 2026). Shared themes are navigation hints; they have not been verified as the same need or independent corroboration.
Adoption decision
Evaluate it against the tool or manual workflow it would replace. The stored record supports discovery; it does not yet establish reliability, lower operating cost or commercial adoption.
Unverified requirements
Not verified: license permissions, required hardware, installation steps, maintenance status and a representative task with its failure cases.
Next test
Choose one real task and a current alternative. Record the commit, environment, input, output, elapsed time and failure behavior; retain the result before recommending adoption.