Two classifiers based on nearest feature plane for recognition
Qingxiang Feng, Jeng‐Shyang Pan, Lijun Yan · 2013
In this paper, two improved methods based on nearest feature plane (NFP), called as center-based nearest feature plane (CNFP) and line-based nearest feature plane (LNFP), are proposed for recognition. Borrowing the concept from the nearest neighbor plane (NNP) classifier and center-based nearest neighbor (CNN) classifier, the proposed methods choose the valuable representation of the class to reduce the computational complexity of NFP. At the same time, CNFP and LNFP try their best to get the better performance than NFP classifier. A large number of experiments on Yale face database and soil object database are used to evaluate the proposed algorithms. The experimental result demonstrate that the proposed method take lower computational complexity and achieve better recognition rate than the other improved classifiers.