A Novel Non-Invasive Method for Extraction of Geometrical and Texture Features of Wood

Abstract

Non invasive feature detection in wood based application requires exact discrimination between geometrical edges and texture. It has been found that traditional edge detection algorithms are highly sensitive to noise and texture and produces inferior results with wood. The present work encompasses a micro level reconstruction of Palash and Rosewood by using micro X-rays CT scanner. It also encompasses a new edge detection algorithm using newly constructed Chebyshev polynomial based fractional order differentiator. Transform based method has been used for reconstruction purpose. Newly designed fractional order filter has been applied on these reconstructed images. Chebyshev polynomial based fractional order differentiator has been used for filtering operation. Quadrature Mirror Filter (QMF) concept has been used for design of high pass filter and low pass filter. Preprocessing has been performed by using this filter. Canny edge detection algorithm has been used on this preprocessed image. The algorithm has been tested on two different test cases of wood images a) Palash and b) Rosewood. The effect of relaxation coefficient has also been presented and discussed. © 2017 American Society for Nondestructive Testing.