The objective of this paper is to develop a Non Destructive Testing (NDT) method for the detection and classification of defects in composite materials at a micro level and to devise methodologies to analyse the corrosion resistance behavior using Scanned Electron Microscope (SEM) imagery. The defects on the Stainless Steel – Molybdenum (SS-Mo) Nanocomposite coating is estimated from their Scanning Electron Micrographs by using Image Processing algorithms. For this, the SS-Mo Nano Composite coatings are fabricated using a DC magnetron sputtering process using an indigenously prepared sputtering target. Depositions are carried out on Glass substrate for the evaluation of structural, morphological, chemical composition and corrosion resistance of the coatings prepared under different conditions (deposition of SS at 300°C and RT (Room Temperature); deposition of SS + Mo at 300°C and RT). The structural and compositional analysis performed with X-ray Diffraction (XRD) and Energy-Dispersive X-ray spectroscopy (EDX) has confirmed the formation of Stainless Steel Molybdenum Composite, when the deposition is at 300°C. The SS-Mo composite deposited at 300°C is also observed to yield high corrosion resistance of the order 0.058 mm/year. A novel texture – morphology based image feature descriptor has been proposed for corrosion resistance to evaluate the composite material in a Non-destructive manner. The analysis of SEM image of the developed coatings using the proposed feature along with machine learning algorithm reveals the superior property for SS-Mo coatings deposited at 300°C which is also demonstrated by the laboratory experiments.