Multi-modal fusion combines multiple modal information to overcome the limitation of
incomplete information expressed by a single modality, so as to realize the complementarity …

Like bilateral filter (BF), cross bilateral filter (CBF) considers both gray-level similarities and
geometric closeness of the neighboring pixels without smoothing edges, but it uses one …

Increasing operational and security demands changed biometrics by shifting the focus from
single to multi-biometrics. Multi-biometrics are mandatory in the current context of large …

The energy compaction and multiresolution properties of wavelets have made the image
fusion successful in combining important features such as edges and textures from source …

For any pattern classification task, an increase in data size, number of classes, dimension of
the feature space, and interclass separability affect the performance of any classifier. A …

This paper presents a framework of a medical image analysis system for the brain tumor
segmentation and the brain tumor following-up over time using multi-spectral MRI images …

Learning from imbalanced data is a challenging problem in many real-world machine
learning applications due in part to the bias of performance in most classification systems …

In this paper we present a new robust approach for 3D face registration to an intrinsic
coordinate system of the face. The intrinsic coordinate system is defined by the vertical …

Bimodal biometrics has been found to outperform single biometrics and are usually
implemented using the matching score level or decision level fusion, though this fusion will …

In medical imaging using different modalities such as MRI and CT, complementary
information of a targeted organ will be captured. All the necessary information from these …