TSL color space

Proposed by Jean-Christophe Terrillon and Shigeru Akamatsu,[1] TSL color space was developed primarily for the purpose of face detection.

Removing the special case produces a system that deviates from the original paper but preserves the sign.

The advantages of TSL color space lie within the normalization within the RGB-TSL transform.

Utilizing normalized r and g allows for chrominance spaces TSL to be more efficient for skin color segmentation.

A Self-Organizing Map (SOM) was implemented in skin detection using TSL and achieved comparable results to older methods of histograms and Gaussian mixture models.