Version 1
: Received: 11 October 2016 / Approved: 11 October 2016 / Online: 11 October 2016 (14:42:02 CEST)
How to cite:
Yang, A.; Han, Y.; Li, J.; Pan, Y.; Shen, L.; Long, Y.; Zhang, Y. Research on an SVM Coupling Algorithm of Image Recognition. Preprints2016, 2016100038. https://doi.org/10.20944/preprints201610.0038.v1
Yang, A.; Han, Y.; Li, J.; Pan, Y.; Shen, L.; Long, Y.; Zhang, Y. Research on an SVM Coupling Algorithm of Image Recognition. Preprints 2016, 2016100038. https://doi.org/10.20944/preprints201610.0038.v1
Yang, A.; Han, Y.; Li, J.; Pan, Y.; Shen, L.; Long, Y.; Zhang, Y. Research on an SVM Coupling Algorithm of Image Recognition. Preprints2016, 2016100038. https://doi.org/10.20944/preprints201610.0038.v1
APA Style
Yang, A., Han, Y., Li, J., Pan, Y., Shen, L., Long, Y., & Zhang, Y. (2016). Research on an SVM Coupling Algorithm of Image Recognition. Preprints. https://doi.org/10.20944/preprints201610.0038.v1
Chicago/Turabian Style
Yang, A., Yan Long and Yu-Zhu Zhang. 2016 "Research on an SVM Coupling Algorithm of Image Recognition" Preprints. https://doi.org/10.20944/preprints201610.0038.v1
Abstract
The key links of face recognition are digital image preprocessing, facial feature extraction and pattern recognition, this article aimed at the current problem of slow speed and low recognition accuracy of face recognition , from the above three key links, on the basic of analyzing the therories of Fractional Differential Masks Operator (FDMO), Principal Component Analysis (PCA) and Support Vector Machine (SVM), design a kind of FDMO+PVA+SVM coupling algorithm that applies to face recognition to improve the speed and accuracy of it. To realize FDMO+PCA+SVM coupling algorithm, first, we should apply FDMO to face image processing binary marginalization, the purpose is getting face contour; Then, we apply PCA to get the feature of face image which is disposed by binary marainalization. At last, we can apply One-Against All of the SVM classifier and LibSVM software package to realize face recognition. Beside, the article with nine different coupling algorithm design four groups of experimental reaults on the ORL face database verified by comparative analysic FDMO+PCA+SVM coupling algorithm in the superiority of face recognition accuracy and speed.
Keywords
Face Recognition; Intelligent Coupling Algorithm; Robustnes; Accuracy; Speed
Subject
Computer Science and Mathematics, Data Structures, Algorithms and Complexity
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.