Surface roughness measurement based on singular value decomposition of objective speckle pattern

Abstract

Roughness being a crucial feature of the surface texture is estimated through numerous techniques. The laser speckle imaging method has emerged as an efficient non-contact tool in the regime of surface roughness measurement techniques. This work presents singular value decomposition-based roughness measurement using objective speckle patterns of the machined surfaces. The surface roughness is quantified as a function of a proposed metric which is the exponential decay rate of the singular values associated with the speckle pattern. The effect of surface correlation length on the proposed metric is investigated and compared with speckle contrast and bright to dark pixel ratio of the binarized speckle pattern. The experimental results demonstrate the broad range surface roughness measuring capability of the proposed method using a single laser source.