  Periodicity of a texture is one of the important visual characteristics and
is often used as a measure for textural discrimination at the structural level.
Knowledge about periodicity of a texture is very essential in the field of
texture synthesis and texture compression and also in the design of frieze and
wall papers. In this paper, we propose a method of periodicity extraction from
noisy images based on superposition of distance matching function (DMF) and
wavelet decomposition without de-noising the test images. Overall DMFs are
subjected to single-level Haar wavelet decomposition to obtain approximate and
detailed coefficients. Extracted coefficients help in determination of
periodicities in row and column directions. We illustrate the usefulness and
the effectiveness of the proposed method in a texture synthesis application.
