Signal period analysis based on Hilbert-Huang transform and its application to texture analysis

An approach to analyze the period of a signal based on Hilbert-Huang transform is presented in this paper. For an approximately periodic signal which contains plenty of high frequency components, the relation between its period and its main frequency is established. Our main result is that, for an approximately periodic signal which contains plenty of high frequency components, its period can be estimated accurately according to its main-frequency distribution. By applying the technique on texture analysis, a novel method to extract the periodicity features of a texture image is developed, which can be used in texture classification, segmentation, recognition and other applications.