Broken Character Image Restoration Using Genetic Snake Algorithm: Deep Concavity Problem
作者: Qusay Omran MosaMohammad Faidzul Nasrudin
刊名: Journal of Computer Science, 2016, Vol.12 (2), pp.81-87
来源数据库: Science Publications
DOI: 10.3844/jcssp.2016.81.87
原始语种摘要: 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contours also known as snakes became a familiar and widely used in the field of image segmentation and restoration of historical documents in last few decades.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 Deep concavity problem it has become Obstacle faced GVF snake when restoring broken characters of historical documents.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.
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  • snake 
  • segmentation 分段
  • algorithm 算法
  • concavity 凹度
  • documents 单据
  • drawback 回火
  • right 右边的
  • restoration 复原
  • adding 求和
  • optimize 优选