Signature recognition by using complex-moments characterisics
Other Title(s)
تمييز التواقيع باستخدام خصائص العزوم المعقدة
Joint Authors
Naum, Riyad Shakir
Jurj, Luayy Idwar
Musa, Ali Kazim
Source
Issue
Vol. 43, Issue 3 (31 Dec. 2002), pp.11-23, 13 p.
Publisher
University of Baghdad College of Science
Publication Date
2002-12-31
Country of Publication
Iraq
No. of Pages
13
Main Subjects
Information Technology and Computer Science
Abstract EN
The complex-moments (CMs) characteristics were considered as an efficient set of parameters describing the geometrical behavior and distribution of the brightness of the image elements.
This fact was recently exploited via the suggestion that the complex-moments characteristics could be utilized as an efficient tool in the discrimination process (i.e.
matching process) to recognize the different objects belong to certain set of images (like, a set of characters, or some uniformly shaped mechanical tools...etc.) Although different geometrical methods was proposed to perform the objects recognition, but in comparison with the complex-moments method they have shown some shortage versus the limited geometrical deformation (caused by rotation, scaling....etc.) may occur during the imaging process.
In this paper, a quantitative analysis was devoted to discuss the efficiency of using the complex-moments characteristics to recognize signatures.
Different types of complex moments were tested in order to identify their relative efficiency and.
consequently, identifying the type of complex-moments could be recommended to properly signature recognition tacks.
American Psychological Association (APA)
Naum, Riyad Shakir& Jurj, Luayy Idwar& Musa, Ali Kazim. 2002. Signature recognition by using complex-moments characterisics. Iraqi Journal of Science،Vol. 43, no. 3, pp.11-23.
https://search.emarefa.net/detail/BIM-595648
Modern Language Association (MLA)
Musa, Ali Kazim…[et al.]. Signature recognition by using complex-moments characterisics. Iraqi Journal of Science Vol. 43, no. 3 (2002), pp.11-23.
https://search.emarefa.net/detail/BIM-595648
American Medical Association (AMA)
Naum, Riyad Shakir& Jurj, Luayy Idwar& Musa, Ali Kazim. Signature recognition by using complex-moments characterisics. Iraqi Journal of Science. 2002. Vol. 43, no. 3, pp.11-23.
https://search.emarefa.net/detail/BIM-595648
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 22
Record ID
BIM-595648