Synergy of foreground–background images for feature extraction: Offline signature verification using Fisher vector with fused KAZE features
作者：
Highlights：
• KAZE features from foreground and background signature images show good performance.
• Fused KAZE features with representation-level fusion further improve performance.
• FV provides a more precise spatial distribution of the characteristics per writer.
• PCA for the FV provides a more compact vector without significant performance loss.
• This method yields lower error rates than existing signature verification systems.
摘要
•KAZE features from foreground and background signature images show good performance.•Fused KAZE features with representation-level fusion further improve performance.•FV provides a more precise spatial distribution of the characteristics per writer.•PCA for the FV provides a more compact vector without significant performance loss.•This method yields lower error rates than existing signature verification systems.
论文关键词：Biometrics,Forensics,Signature verification,Fisher vector,KAZE features,Fusion strategy,Support vector machine
论文评审过程：Received 5 July 2017, Revised 21 February 2018, Accepted 25 February 2018, Available online 27 February 2018, Version of Record 6 March 2018.
论文官网地址：https://doi.org/10.1016/j.patcog.2018.02.027
