# Summed-area table vs Integral image?

I have been going through few research papers around face recognition and I came across two texture extraction algorithms :

1. Summed-area table by Crow et al. ("Summed-area tables for texture mapping", 1984)
2. Integral image by Viola et al. (e.g. "Robust Real-time Object Detection", 2002)

Apologizes if I'm wrong, I found that generating texture map in both these algorithms are same.

i.e., Texture map $I(x,y)$ = Sum of all gray level intensity values who lies left and above $i(x,y)$ of the original image.

Please clarify me, what is the main difference between these two algorithms?