Improved algorithm of separation and identification of touching kernels and foreign materials in digital images

Abstract

An improved method of separation and identification of touching kernels and foreign materials in digital images is proposed. The touching kernels are separated by using watershed algorithm based on morphological multiscale decomposition (MSD). Then, feature extraction of kernels is used for calculation of Mahalanobis distance. Finally foreign materials are identified by comparing Mahalanobis distance with the given threshold. The performance of the new algorithm is compared to that of a method based on a watershed algorithm and Mahalanobis distance (WMD). The experimental results showed that the efficiency of the proposed algorithm was superior with regard to WMD. © 2011 Springer-Verlag Berlin Heidelberg.