  Quantization of a probability distribution is the process of estimating a
given probability by a discrete probability that assumes only a finite number
of levels in its support. Centroidal Voronoi tessellations (CVT) are Voronoi
tessellations of a region such that the generating points of the tessellations
are also the centroids of the corresponding Voronoi regions. In this paper, we
investigate the optimal quantization and the centroidal Voronoi tessellations
with $n$ generators for a Borel probability measure $P$ on $\mathbb R$
supported by a dyadic Cantor set generated by two self-similar mappings with
similarity ratios $r$, where $0<r\leq \frac{5-\sqrt{17}}2$.
