Sets of unit vectors in

-dimensional Euclidean vector space whose constituent vectors are separated one from another by at least a fixed distance

, prescribed once for all and independent of

, are of interest in theory and practice; they have fondly been called "porcupine codes." Although an elegant constructive proof of Gilbert shows that the number of vectors in a porcupine code (of given

) can increase exponentially with

, no systematic method is yet known for generating porcupine codes of this cardinality. Corresponding to a collection of

vectors, we can partition the space into maximum-likelihood regions, the

th of which consists of those vectors that lie closer to the

th than to any other element of the collection. Each maximum-likelihood region is bounded by at most

hyperplanes, and we denote by

the total number of these bounding hyperplanes. Collections for which

is small may be expected to have greater symmetry than those for which

is large. In this paper we show that, for porcupine codes,

, with

depending only on

, the minimum separation of the code vectors. Hence, for the number of vectors of a porcupine code to increase exponentially with dimension, the number of separating hyperplanes must do so as well. We conclude with, an application to the permutation codes introduced by Slepian, showing that the number of vectors of a porcupine code which is of permutation-modulation type can not increase exponentially with

.