Investigation And Analysis of Real Time Transformer oil Images Using Haralick Texture Features

This paper proposes an innovative method in the investigation and analysis of real time transformer oil images at different temperatures along with different ages using haralick image texture features. Haralick texture feature method based on Gray-Level Co-occurrence Matrix (GLCM) used in this paper to enumerate the spatial relation between the neighborhood pixels in an image. A theoretical examination performed on oil test images to characterize its textural properties. The statistical features extracted for original as well as filtered transformer oil image at different temperatures, and features of one year to twenty five year aged oils determined. The results through this analysis indicate the identification of significant textures of the test images. The experimental results demonstrated that texture feature extraction derived from the haralick features realize a new technique in the analysis of transformer oil images under different ages as well as operating conditions.