The Effect of Color Space Selection on Detectability and Discriminability of Colored Objects

TL;DR

This study evaluates how different color spaces affect the detectability and discriminability of colored objects, revealing no single best space but highlighting the effectiveness of C1C2C3, UVW, and XYZ in various conditions.

Contribution

The paper provides a comprehensive evaluation of 20 color spaces on a large dataset, introduces a new dataset of simulated 3D objects, and demonstrates practical benefits in active visual search.

Findings

No single color space is optimal for all color groups.

C1C2C3, UVW, and XYZ perform best overall.

Proper color space choice can reduce search time by 20%.

Abstract

In this paper, we investigate the effect of color space selection on detectability and discriminability of colored objects under various conditions. 20 color spaces from the literature are evaluated on a large dataset of simulated and real images. We measure the suitability of color spaces from two different perspectives: detectability and discriminability of various color groups. Through experimental evaluation, we found that there is no single optimal color space suitable for all color groups. The color spaces have different levels of sensitivity to different color groups and they are useful depending on the color of the sought object. Overall, the best results were achieved in both simulated and real images using color spaces C1C2C3, UVW and XYZ. In addition, using a simulated environment, we show a practical application of color space selection in the context of top-down control in active visual search. The results indicate that on average color space C1C2C3 followed by HSI and XYZ achieve the best time in searching for objects of various colors. Here, the right choice of color space can improve time of search on average by 20%. As part of our contribution, we also introduce a large dataset of simulated 3D objects