We investigated the asymptotics of high-rate constrained quantization errors for a compactly supported probability measure P on Euclidean spaces whose quantizers are confined to a closed set S. The key tool is the metric projection of K onto S that assigns each source point to its nearest neighbor in S, allowing the errors to be transferred to the projection, where K = supp P. For the upper estimate, we establish a projection pull-back inequality that bounds the errors by the classical covering radius of the projection. For the lower estimate, a weighted distance function enables us to perturb any quantizer element lying on the projection slightly into the complement in S without enlarging the error, provided the projection is nowhere dense (automatically true when S and K are disjoint). Under mild conditions on the pushforward measure of P by T, obtained via a measurable selector T, we derive a uniform lower bound. If this set is Ahlfors regular of dimension d, the error decays like the reciprocal of the d-th root of n and every constrained quantization dimension equals d. The two estimates coincide, giving the first complete dimension comparison formula for constrained quantization and closing the gap left by earlier self-similar examples by Pandey-Roychowdhury while extending classical unconstrained theory to closed constraints under mild geometric assumptions.