Palette-based Image Search with Color Weights
Naoki Kita, Shiori Kawasaki, Takafumi Saito · 2022
We propose a novel image search system with color palettes. By querying color palettes, users can search for inspiring images, which is helpful for design exploration. Although few such systems can accept palettes as queries, they have several constraints on query palettes (e.g., limited palette size) or search results. Our system accepts palettes with color weights and any sizes as the inputs and returns results with enough diversity that can stimulate users’ design inspiration. To achieve these, we extract color themes from our database with a perceptually-based model and calculate the palette similarity based on a weighted palette distance. Visual comparisons demonstrate that our system has more potential for helping users’ design inspiration than the existing systems.