We study the construction of structured regular quantizers for overcomplete expansions in RN. Our goal is to design structured quantizers allowing simple reconstruction algorithms with low (memory and computational) complexity and having good performance in terms of accuracy. Most related work to date in quantized redundant expansions has assumed that uniform scalar quantization with the same stepsize was used on the redundant expansion and then has dealt with more complex methods to improve the reconstruction. Instead, we consider the design of scalar quantizers with different stepsizes for each coefficient of an overcomplete expansion in such a way as to produce an equivalent vector quantizer with periodic structure. The periodicity makes it possible to achieve good accuracy using simple reconstruction algorithms from the quantized coefficients of the overcomplete expansion.