Pattern Recognition

Feature selection in the data with different types of feature values, i.e., the heterogeneous or mixed data, is especially of practical importance because such types of data sets widely exist in real world. The key issue for feature selection in mixed ...

Zernike moments and Zernike polynomials have been widely applied in the fields of image processing and pattern recognition. When high-order Zernike moments are computed, both computing speed and numerical accuracy become inferior. The main purpose of ...

In this paper, we present the Delta Medial Axis (DMA), a quasi-linear algorithmic solution addressing several of the main concerns of discrete medial axes (MA) computation. First, its sensitivity to small shape perturbations is counterbalanced by a ...

This paper presents a novel quadratic projection based feature extraction framework, where a set of quadratic matrices is learned to distinguish each class from all other classes. We formulate quadratic matrix learning (QML) as a standard semidefinite ...

Despite fuzzy commitment (FC) is a theoretically sound biometric-key binding scheme, it relies on error correction code (ECC) completely to mitigate biometric intra-user variations. Accordingly, FC suffers from the security-performance tradeoff. That is,...

This paper focuses on extending the capabilities of relevance vector machine which is a probabilistic, sparse, and linearly parameterized classifier. It has been shown that both relevance vector machine and support vector machine have similar ...

In image classification, can sparse representation (SR) associate one test image with all training ones from the correct class, but not associate with any training ones from the incorrect classes? The backward sparse representation (bSR) which contains ...

Among the challenges faced by current active shape or appearance models, facial-feature localization in the wild, with occlusion in a novel face image, i.e. in a generic environment, is regarded as one of the most difficult computer-vision tasks. In ...

This paper deals with a new expression recognition method by representing facial images in terms of higher-order two-dimensional orthogonal Gaussian-Hermite moments (GHMs) and their geometric invariants. Only the moments having high discrimination power ...

Singular point is an essential global feature in fingerprint images. Existing methods for singular points' detection generally visit each pixel or each small image block to determine the singular point. That is to say, existing methods require scanning ...

Incorporating models of human perception into the process of scene interpretation and object recognition in visual content is a strong trend in computer vision. In this paper we tackle the modeling of visual perception via automatic visual saliency maps ...

In many real classification scenarios the distribution of test (target) domain is different from the training (source) domain. The distribution shift between the source and target domains may cause the source classifier not to gain the expected accuracy ...

An unsupervised learning algorithm with density information considered is proposed for congested scene classification. Though many works have been proposed to address general scene classification during the past years, congested scene classification is ...

Many hierarchical multi-label classification systems predict a real valued score for every (instance, class) couple, with a higher score reflecting more confidence that the instance belongs to that class. These classifiers leave the conversion of these ...