ガイド
画像から色を抽出するときのよくある失敗
ノイズの多い配色や不安定な判断につながるミスを防ぎます。
抽出は手軽ですが、元画像や選び方が悪いと使いにくいパレットになります。
Mistake: sampling low-quality images
Compression artifacts distort extracted colors.
Always start with the highest quality image you can access.
Mistake: collecting too many similar colors
Large noisy palettes are hard to use consistently.
Merge near-duplicates into a smaller practical set.
Mistake: skipping context and contrast checks
Extracted colors may look good in isolation but fail in interfaces.
Test text readability and UI state combinations early.
- Run contrast checks.
- Preview on real components.
- Validate light and dark surfaces.
Mistake: no naming or documentation
Unnamed colors are difficult to reuse across teams.
Assign role-based names and capture final approved values.
Watch out during
- Palette creation.
- Brand approximation.
- Photo-based UI theming.
Better inputs produce better palettes
Use clean images, sample intentionally, and validate before rollout.