Automatic Extraction of Texture-Periodicity Using Superposition of Distance Matching Functions and First Forward Difference

In this paper, we propose a method of automatic detection of texture-periodicity using superposition of distance matching functions (SDMF) followed by computation of their first forward differences. The method has been specifically devised for automatically identifying row and column periodicities and thereby the size of periodic units is achieved. Overall row (or column) distance matching functions (DMF) is obtained based on SDMF of all rows (or columns) from the input image and its first forward difference is computed to get the mode of periodic sequence which is a direct measure of periodicity along row (or column) direction. Results from experiments on various near-regular textures demonstrate the performance of the proposed method for automatic periodicity extraction.