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In order to further improve the recognition rate and computing efficiency of modular 2DPCA in face recognition, an improved modular 2DPCA method based on image segmentation is proposed. Firstly, segmentation of threshold value optimization is utilized to segment face image of training samples into several non-overlapping sub-image spaces so that the pixel number has uniform distribution in each sub-image...
Feature selection plays an important role in text categorization. Classic feature selection methods such as document frequency (DF), information gain (IG), mutual information (MI) are commonly applied in text categorization. But usually they only take plain text into account. Knowledge Gain (KG) is a new feature selection method which is proposed in my previous paper. It measures attribute's importance...
In recent years, microblog has been experiencing an explosive growth, which brings much inconvenience to users to build a healthy social circle in this chaos online world. Friend recommendation can automatically recommend potential friends, filter out the useless information, and facilitate the healthy development of social network. A novel friend recommendation approach is proposed in this paper...
In this paper, we propose a novel palmprint verification scheme named as Orthogonal Code based on multiple 2D Orthogonal Gabor Phase feature. A palmprint image contains various features with multiple orientations, so only a single orientation in the palmprint can not distinguish a subject well. The 2D Orthogonal Gabor filters with different orientations are employed to extract texture information...
In this paper, a new algorithm of face detection based on differential images and PCA in color image is proposed which modified the eigenface technique. First, skin picking-up is carried out by color analysis of an image. Then, for finding the exact positions of faces, a finer matching is performed by eigenface in these detected fields and a mosaic template is used to suppress the false face. Considering...
Facial images with high dimension often belong to a manifold of intrinsically low dimension. Subspace methods utilize different algorithms to extract and analyze the underlying manifold for face recognition. Isomap is a recently proposed algorithm for manifold learning and nonlinear dimensionality reduction. However, since the Isomap is developed based on minimizing the reconstruction error with multi-dimensional...
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