Non contact method for surface roughness measurement for quality estimation using image processing techniques

Abstract

Surface roughness parameters have major role in estimating the quality of the surface finish product during manufacturing processes. It has great importance in manufacturing fields such as ceramic tiles, glass, wood and iron. Conventionally, measurement of the surface roughness parameters is done with a surface profile-meter consisting of a contact stylus. Since this measurement process is contact type and it is not suitable for automation, over the last few years, advances in image processing techniques have been developed and have provided a basis for developing surface roughness measurement techniques using image processing. In this research work, we have proposed a novel technique to measure the surface roughness parameters of ceramic tile surfaces using image processing. newlineIn this proposed technique, firstly the surface image of the work pieces is acquired using the digital camera and image pre-processing is carried on. The step involved in pre-processing are image resizing, RGB to Grey conversion, filtering for noise removal. A pixel density based trimmed median filter for reduction of noise in images is proposed. The performance of the proposed filter was compared with other filters like adaptive weighted mean filter (AWMF), Decision Based Unsymmetrical Trimmed Variants filter (DBUTVF), modified decision based unsymmetric trimmed median filter (MDBUTMF), Noise Adaptive Fuzzy Switching Median Filter (NAFSMF) and it was observed that better results were obtained using the proposed filter. The proposed algorithm is tested against different grayscale and color images and it gives high Peak Signal-to-Noise Ratio (PSNR), low Mean Square Error (MSE) and better Image Enhancement Factor (IEF), SSIM, Correlation Index. newlineThe denoised imaged is enhanced using various techniques such as AGCWD, ASAUMF, AVGHEQ and MMSICHE. The performance of proposed Bi-histogram based image enhancement with Bicubic interpolation (BHBI) was tested on standard images such as cameraman, lena and some ceramic tiles and wood surface images.