Title :
Extraction and Application of the Signature Biostatistics Features
Author :
Shu-ren, Zhu ; Hui-hui, Hu ; Wei-qin, Li
Author_Institution :
GuangDong Univ. of Bus. Studies, Guangzhou
fDate :
Aug. 30 2006-Sept. 1 2006
Abstract :
The typical features of the coordinate and the curvature as well as the time information recorded were analyzed in the hand-written signatures. In the hand-written signature process 10 biometric features were summarized. The formulae of biometric features extraction were concluded. The Gauss function was used to draw the typical information from the above-mentioned biometric features, with which to establish the HMM and to train it. The training practice indicates that the hand-written signature verification can satisfy the needs from the OA systems
Keywords :
Gaussian processes; feature extraction; handwriting recognition; hidden Markov models; learning (artificial intelligence); Gauss function; HMM training; biometric feature extraction; handwritten signature biostatistics feature extraction; handwritten signature verification; Acceleration; Biometrics; Character recognition; Feature extraction; Frequency estimation; Gaussian processes; Handwriting recognition; Hidden Markov models; Information analysis; Space technology;
Conference_Titel :
Innovative Computing, Information and Control, 2006. ICICIC '06. First International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7695-2616-0
DOI :
10.1109/ICICIC.2006.451