Abstract: A system and associated method automatically and very rapidly determine the dominant periodicity in sequential binary data. The method incorporates a fast binary autocorrelation function used to discover the dominant periodicity in a sequential binary signal, and exploits this information in a periodicity exploiting application, such as using any one or more of a pixel periodicity or an edge periodicity based compression method in order to compress periodic halftoned bitonal images. The method implements four processes: The first process describes setting up the data in a transition-based representation to facilitate an algorithm to quickly find an autocorrelation distribution derived from a sequential binary signal. The second process describes a fast dominant periodicity search algorithm. The third process describes an algorithm that estimates the dominant window for estimating the dominant periodicity within one line of two-dimensional sequential binary signal.

Abstract: A system and associated method automatically and very rapidly determine the dominant periodicity in sequential binary data. The method incorporates a fast binary autocorrelation function used to discover the dominant periodicity in a sequential binary signal, and exploits this information in a periodicity exploiting application, such as using any one or more of a pixel periodicity or an edge periodicity based compression method in order to compress periodic halftoned bitonal images. The method implements four processes: The first process describes setting up the data in a transition-based representation to facilitate an algorithm to quickly find an autocorrelation distribution derived from a sequential binary signal. The second process describes a fast dominant periodicity search algorithm. The third process describes an algorithm that estimates the dominant window for estimating the dominant periodicity within one line of two-dimensional sequential binary signal.