A processor implemented method comprising the steps of: computing, by a controller unit, extrema points within an empirically determined length of a reflected signal, the reflected signal being a signal reflected off a sample material in a sample set in response to a transmitted signal from a Continuous Wave 'CW' radar, wherein the empirically determined length of the reflected signal is 2.5λ, wherein λ represents wavelength of the reflected signal, and wherein the step of computing extrema points comprises: moving the CW radar in steps of λ/10 within the 2.5λ from a starting point being at a distance of at least 6λ from the sample material; measuring a baseband signal B(t) corresponding to the reflected signal at each λ/10 distance; performing a first order derivative of the measured baseband signal B(t); and identifying points where the first order derivative is zero as the extrema points; identifying, by the controller unit, maxima points and minima points from the extrema points by performing a second order derivative thereon; computing, by the controller unit, absolute slope of each line between a maxima point and a consecutive minima point from the identified maxima points and minima points based on associated amplitude and distance of the CW radar from the corresponding sample material; generating, by the controller unit, a first feature set comprising average of slopes computed for a plurality of iterations of the steps of computing the extrema points, identifying the maxima points and the minima points thereof and computing the absolute slope of each line, corresponding to each sample material from the sample set; training, a classifier model, using the generated first feature set; and classifying a material under inspection based on absolute slope computed using any two consecutive extrema points using the trained classifier model. computing, by a controller unit, extrema points within an empirically determined length of a reflected signal, the reflected signal being a signal reflected off a sample material in a sample set in response to a transmitted signal from a Continuous Wave 'CW' radar, wherein the empirically determined length of the reflected signal is 2.5λ, wherein λ represents wavelength of the reflected signal, and wherein the step of computing extrema points comprises: moving the CW radar in steps of λ/10 within the 2.5λ from a starting point being at a distance of at least 6λ from the sample material; measuring a baseband signal B(t) corresponding to the reflected signal at each λ/10 distance; performing a first order derivative of the measured baseband signal B(t); and identifying points where the first order derivative is zero as the extrema points; moving the CW radar in steps of λ/10 within the 2.5λ from a starting point being at a distance of at least 6λ from the sample material; measuring a baseband signal B(t) corresponding to the reflected signal at each λ/10 distance; performing a first order derivative of the measured baseband signal B(t); and identifying points where the first order derivative is zero as the extrema points; identifying, by the controller unit, maxima points and minima points from the extrema points by performing a second order derivative thereon; computing, by the controller unit, absolute slope of each line between a maxima point and a consecutive minima point from the identified maxima points and minima points based on associated amplitude and distance of the CW radar from the corresponding sample material; generating, by the controller unit, a first feature set comprising average of slopes computed for a plurality of iterations of the steps of computing the extrema points, identifying the maxima points and the minima points thereof and computing the absolute slope of each line, corresponding to each sample material from the sample set; training, a classifier model, using the generated first feature set; and