Image segmentation of touching objects plays a key role in providing accurate classification for computer vision technologies. A new line profile based imaging segmentation algorithm has been developed to provide a robust and accurate segmentation of a group of touching corns. The performance of the line profile based algorithm has been compared to a watershed based imaging segmentation algorithm. Both algorithms are tested on three different patterns of images, which are isolated corns, single-lines, and random distributed formations. The experimental results show that the algorithm can segment a large number of touching corn kernels efficiently and accurately.
@article{arxiv.1706.00396,
title = {Line Profile Based Segmentation Algorithm for Touching Corn Kernels},
author = {Ali Mahdi and Jun Qin},
journal= {arXiv preprint arXiv:1706.00396},
year = {2017}
}
Comments
We found some results in this paper may not be correct. Therefore, we require to withdraw this paper. Thanks