Face recognition based on symmetrical NIB2DPCA
Luo Chan-juan · Jisuanji yingyong yanjiu · 2013
This paper proposed a new algorithm called SNIB2DPCA,which combined the theory of NIB2DPCA with frontal facial symmetry.Firstly,it introduced mirror transform.After that,it decomposed original face samples into even symmetrical images and odd symmetrical ones through the theory of odd/even decomposition.Then employed NIB2DPCA to extract feature information from odd and even symmetrical samples separately.After that,combined the odd and even feature matric to form the final feature matric by the odd/even weighted factors.Finally,it employed the nearest neighbor classifier to classify the final feature matric.The method was evaluated on the Yale,ORL and YaleB face image databases.Both theoretical analysis and experimental results demonstrate that the proposed method not only significantly raises the recognition rate,but also has certain robustness to the influence of light.