Off-Line Signature Recognition Based on Angle Features and Artificial Neural Network Algorithm-中国期刊网

摘要 Handwrittensignaturerecognitionispresentedbasedonananglefeaturevectorbyusingtheartificialneuralnetwork(ANN)inthisresearch.Eachsignatureimagewillberepresentedbyananglevector.ThefeaturevectorwillconstitutetheinputtotheANN.Thecollectionofsignatureimagesisdividedintotwosets.OnesetwillbeusedfortrainingtheANNinasupervisedfashion.TheothersetwhichisneverseenbytheANNwillbeusedfortesting.Aftertraining,theANNwillbetestedbyrecognizingthesignatures.Whenasignatureisclassifiedcorrectly,itisconsideredcorrectrecognition,otherwiseitisafailure.Theachievedrecognitionrateofthissystemis94%.

1. mandarin chinese tone recognition with an artificial neural network.耳鼻咽喉科,2006-01.
2. A multi-target approach for isolated word recognition using artificial neural network.声学,1994-02.
3Amin Dastanpour Suhaimi Ibrahim Reza Mashinchi Ali Selamat. Using Genetic Algorithm to Support Artificial Neural Network for Intrusion Detection System.计算机应用技术,2014-02.
4LiuJunfeng LuoHui WanShuyun. Off-Line Identification of Induction Motor Parameters.电机,2005-02.
5NIU Wei-hua. Electric Power Marketing based on intelligence decision tree and artificial Neural Network.计算机应用技术,2008-01.
6Mustapha Boutahri Said El Yamani Samir Zeriouh Abdenabi Bouzid Ahmed Roukhe. Fingerprint Identification by Artificial Neural Network.物理,2014-06.
7JIA Rui-wu SHI Geng-chen. Network boundary recognition via relative azimuth angle.通信与信息系统,2010-04.
8. Neural network processing for adaptive line enhancement.声学,1993-04.
9蒋国荣;张韧;沙文钰;阎俊岳;姚华栋. ARTIFICIAL NEURAL NETWORK CORRECTION OF ROUGH ERRORS OF OBSERVATIONS.大气科学及气象学,2002-01.
10MingxingLi PingHeng PeiwuDong. Research on Artificial Neural Network Method for Credit Application.系统科学,2004-01.

Off-Line Signature Recognition Based on Angle Features and Artificial Neural Network Algorithm

来源期刊

相关推荐

同分类资源更多

相关关键词

Off-Line Signature Recognition Based on Angle Features and Artificial Neural Network Algorithm

来源期刊

相关推荐

同分类资源 更多

相关关键词

同分类资源更多