Palmprint Recognition Using Different Level of Information Fusion


  • Siti Nur Wasilah Mohd Zuki School of Computer and Communication Engineering, Universiti Malaysia Perlis, KampusPauh Putra, 02600, Perlis
  • Muhammad Imran Ahmad School of Computer and Communication Engineering, Universiti Malaysia Perlis, KampusPauh Putra, 02600, Perlis
  • Ruzelita Ngadiran School of Computer and Communication Engineering, Universiti Malaysia Perlis, KampusPauh Putra, 02600, Perlis
  • Mohd Nazrin Md Isa School of Microelectronic Engineering, Universiti Malaysia Perlis, KampusPauh Putra, 02600, Perlis


Biometric System, Palmprint Recognition,


The aim of this paper is to investigate a fusion approach suitable for palmprint recognition. Several number of fusion stageis analyse such as feature, matching and decision level. Fusion at feature level is able to increase discrimination power in the feature space by producing high dimensional fuse feature vector. Fusion at matching score level utilizes the matching output from different classifier to form a single value for decision process. Fusion at decision level on the other hand utilizes minimal information from a different matching process and the integration at this stage is less complex compare to other approach. The analysis shows integration at feature level produce the best recognition rates compare to the other method.


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How to Cite

Mohd Zuki, S. N. W., Ahmad, M. I., Ngadiran, R., & Md Isa, M. N. (2016). Palmprint Recognition Using Different Level of Information Fusion. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 8(4), 139–144. Retrieved from