Partition-based Face Recognition Using LDP and SVM

Authors

  • Faizaullah . Lecturer, Department of Computer Science, Bacha Khan University Charsadda, KPK, Pakistan
  • Sabir Shah Lecturer, Department of Computer Science, Bacha Khan University Charsadda, KPK, Pakistan
  • Dilawar Shah Assistant Professor, Department of Computer Science Bacha Khan University Charsadda, KPK, Pakistan

Keywords:

Face Recognition, Support Vector Machine (SVM,) Local Directional Pattern (LDP),, Active Shape Model (ASM), Spatial Coordinate System.

Abstract

In this paper, an efficient face recognition algorithm has been presented. First, the face image is extracted to reduce the data dimensions. Next, five important facial components are located using Active Shape Model (ASM). Features from these important components are extracted using Local Directional Pattern (LDP). In the recognition module, Support Vector Machine (SVM) is used to train and tested on the resultant features. The high recognition rate of 97% has been obtained by utilizing a minimum number of features using ORL face database. The results of the proposed technique are substantially accurate.

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Published

2018-12-09

Issue

Vol.8 No.1(2017): January-June

Section

Original Articles

How to Cite

[1]
F. ., S. Shah, and D. Shah, “Partition-based Face Recognition Using LDP and SVM”, jictra, pp. 37–43, Dec. 2018, Accessed: Mar. 23, 2025. [Online]. Available: https://jictra.com.pk/index.php/jictra/article/view/9