Abstract:
This work explores human-assisted schemes for improving automatic signature recognition systems. We present a crowdsourcing experiment to establish the human baseline per...Show MoreMetadata
Abstract:
This work explores human-assisted schemes for improving automatic signature recognition systems. We present a crowdsourcing experiment to establish the human baseline performance for signature recognition tasks and a novel attribute-based semi-automatic signature verification system inspired in FDE analysis. We present different experiments over a public database and a self-developed tool for the manual annotation of signature attributes. The results demonstrate the benefits of attribute-based recognition approaches and encourage to further research in the capabilities of human intervention to improve the performance of automatic signature recognition systems.
Date of Conference: 29 February 2016 - 02 March 2016
Date Added to IEEE Xplore: 26 May 2016
ISBN Information: