# Multiple Light Source Dataset for Colour Research

## TL;DR

This paper introduces a comprehensive dataset of 24 scenes under 18 different lighting conditions, designed for evaluating colour constancy and segmentation algorithms in realistic scenarios.

## Contribution

It provides a diverse, annotated dataset with spectral data and ground truth for benchmarking colour research and computer vision tasks.

## Key findings

- Dataset covers varied spectral colours, intensities, and distances.
- Includes pixel-level ground truth for colour segmentation.
- Facilitates evaluation of colour constancy algorithms.

## Abstract

We present a collection of 24 multiple object scenes each recorded under 18 multiple light source illumination scenarios. The illuminants are varying in dominant spectral colours, intensity and distance from the scene. We mainly address the realistic scenarios for evaluation of computational colour constancy algorithms, but also have aimed to make the data as general as possible for computational colour science and computer vision. Along with the images of the scenes, we provide spectral characteristics of the camera, light sources and the objects and include pixel-by-pixel ground truth annotation of uniformly coloured object surfaces thus making this useful for benchmarking colour-based image segmentation algorithms. The dataset is freely available at https://github.com/visillect/mls-dataset.