Perhaps the most straightforward classifier in the arsenal or Machine Learning techniques is
the Nearest Neighbour Classifier—classification is achieved by identifying the nearest …

This paper compares principal component analysis (PCA) and independent component
analysis (ICA) in the context of a baseline face recognition system, a comparison motivated …

Perhaps the most straightforward classifier in the arsenal or machine learning techniques is
the Nearest Neighbour Classifier--classification is achieved by identifying the nearest …

Face recognition is one of the most successful applications of image analysis and
understanding and has gained much attention in recent years. Various algorithms were …

Recently, biometric palmprint has received wide attention from researchers. It is well-known
for several advantages such as stable line features, low-resolution imaging, low-cost …

We present a comprehensive performance study of multiple appearance-based face
recognition methodologies, on visible and thermal infrared imagery. We compare algorithms …

Principal components analysis (PCA) is a standard tool in multivariate data analysis to
reduce the number of dimensions, while retaining as much as possible of the data's …

This work is a continuation and extension of our previous research where kernel Fisher
discriminant analysis (KFDA), a combination of the kernel trick with Fisher linear discriminant …

In this paper, we propose a novel subspace method called Fisher non-negative matrix
factorization (FNMF) for face recognition. FNMF is based on non-negative matrix …

图像特征提取是图像识别的关键步骤, 图像特征提取的效果如何直接决定着图像识别的效果.
如何从原始图像中提取具有较强表示能力的图像特征是智能图像处理的一个研究热点 …