Visual railway detection by superpixel based intracellular decisions

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• 作者：Zhu Teng ; Feng Liu ; Baopeng Zhang
• 关键词：Railway detection ; Superpixel ; Intracellular decision scheme
• 刊名：Multimedia Tools and Applications
• 出版年：2016
• 出版时间：March 2016
• 年：2016
• 卷：75
• 期：5
• 页码：2473-2486
• 全文大小：1,859 KB
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• 作者单位：Zhu Teng (1)
  Feng Liu (1)
  Baopeng Zhang (1)
  
  1. School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China
  
• 刊物类别：Computer Science
• 刊物主题：Multimedia Information Systems
  Computer Communication Networks
  Data Structures, Cryptology and Information Theory
  Special Purpose and Application-Based Systems
  
• 出版者：Springer Netherlands
• ISSN：1573-7721

文摘

Safety is one of the most concerned issues in traffic and transportation, among which railway detection is a fundamental and necessary research. In this paper, we propose a visual railway detection method based on superpixels rather than pixels. An SVM classifier is learned based on features, on which a TF-IDF like transform is applied, and it greatly improves the performance of the classification. The intracellular decision scheme is proposed to make decisions on a superpixel by using predictions of features within the superpixel. All the superpixels that are predicted as positive constitute the railway to be detected. The proposed railway detection method is evaluated on a number of challenging images and experiments demonstrate that the proposed method is an effective and detailed solution to railway detection, and is superior to other railway detection methods.