Does segmentation algorithms perform better in frequency domain than spatial domain?

I am implementing a published paper, where cellular region needs to be segmented from non-cellular region in a microscopic image of human cells. In the paper LFT coefficients of each pixel are selected as the features. And K-NN is used for segmentation. I am looking for reason, why RGB values are not selected directly as features, and applied K-NN on them? I have tested the same procedure using RGB values, but the segmentation quality was better using LFT features than RGB features. Can someone explain why segmentation worked better in frequency domain than in spatial domain? I understand why frequency domain in better for filtering.