Texture classification of complex vector vortex beams

Abstract

Abstract. Transverse spatial structure associated to complex vector vortex beams (VVBs) is classified through an image texture approach, which is based on Haralick features derived from an azimuthally sensitive gray-level co-occurrence matrix (a-GLCM). Previously, the proposed texture identifier has been tested on azimuthally symmetric digital images presenting an improvement in comparison with conventionally constructed GLCM. Then, considering their suitable spatial symmetry, Laguerre–Gauss mode vector beams were numerically generated to characterize its transverse section. Nonetheless, because of the complex structural information, VVBs are decoupled in three 8-bit grayscale images (channels) corresponding to intensity, orientation, and ellipticity parameters. a-GLCMs and Haralick features for each channel are computed with the aim of quantifying transverse structure evolution as a function of topological charge. Also, image scaling effects are studied to test the approach robustness. Even though it has simplicity, texture analysis based on a-GLCM provides an insight to classify VVB structure.