Palmprint Recognition Based on Two-dimensional Fisher Linear Discriminant
Weiqi Yuan · Jisuanji gongcheng · 2008
In the FLD-based recognition, the within-class scatter matrix is always singular. To overcome the above problem, a new way is to directly project the image matrix based on Two-Dimensional FLD(2DFLD). In PolyU palmprint database, this paper applies PCA, PCA+FLD and 2DFLD to extract the palmprint feature subspace. The images to be recognized are projected on small dimension subspace. A classifier to palmprint match based on cosine distance is used. Experimental results show that the recognition rate of PCA+FLD is about 1.18% higher than that of PCA. Compared with PCA+FLD, this method is able to yield recognition rate as high as 99.34%, with accuracy enhanced by 7.61%, while the feature extraction time is only 0.032 s.