@article {10.3844/jcssp.2016.81.87,
article_type = {journal},
title = {Broken Character Image Restoration Using Genetic Snake Algorithm: Deep Concavity Problem},
author = {Mosa, Qusay Omran and Nasrudin, Mohammad Faidzul},
volume = {12},
number = {2},
year = {2016},
month = {Mar},
pages = {81-87},
doi = {10.3844/jcssp.2016.81.87},
url = {https://thescipub.com/abstract/jcssp.2016.81.87},
abstract = {Active contours also known as snakes became a familiar and widely used in the field of image segmentation and restoration of historical documents in last few decades. Gradient Vector Flow (GVF) snake successes in overcome of converge to boundary concavities which represents the drawback of traditional snakes. Deep concavity problem it has become Obstacle faced GVF snake when restoring broken characters of historical documents. In this study we proposed algorithm to use genetic algorithm with GVF snake algorithm in order to optimize snake points to get right positions in deep concavity boundaries, also adding a Divergence factor as the third force to enhance the restoring and recognizing results. The experimental results show that our proposed algorithm has more capture than GVF alone.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}