JuliaImages / JuliaImages/juliaimages.github.io
Tutorial on image gradients
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- Dominant language
- Julia
- Stars
- 33
- Forks
- 52
- PR merge metrics
- No merged PRs in 30d
Description
I recently was reviewing ImageCorners.jl and it uses imgradient a lot, and there exist of lot of different types of filter like prewitt, sobel etc that are utilized. I would wanna introduce readers to:
- gradient in general
- gradient for a 2d signal, (grad_x, grad_y)
- gradient orientation and magnitude and help visualize
- gradient operator([grad_x, grad_y]) this is going to be useful later I know
- compare finite differences method and ForwardDiff
- basic edge thresholding
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reviewing ImageCorners.jl and the existing use of imgradient, including the available Prewitt and Sobel filters. A finished tutorial should cover 2D gradients, orientation and magnitude visualization, gradient operators, finite differences versus ForwardDiff, and basic edge thresholding.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- computer-vision, documentation
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100