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Co-Occurrence Matrix and Its Statistical Features as an Approach for Identification Of Phase Transitions Of Mesogens

Abstract

Statistical features extracted from the Gray Level Co-occurrence Matrix (GLCM) of liquid crystal textures are used to investigate the phase transition temperatures of nematic liquid crystals p – n Alkyl benzoic acids (nBA) where n = 8,9 and10. Textures of compounds are recorded as a function of temperature using Polarizing Optical Microscope attached to the hot stage and high resolution camera. In this method, second order statistical parameters – contrast, energy, homogeneity and correlation of the sample textures are computed using MATLAB software. The changes associated in the values of computed statistical features as a function of temperature is a helpful process to identify the phase transition temperatures of the samples. Results obtained from this method are compared with literature values of Differential Scanning Calorimetry (DSC) and are in agreement

C.Nageswara Rao , S.Sreehari Sastry , K.Mallika , Ha Sie Tiong and K.B.Mahalakshmi

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