This paper proposes fusion and addition techniques of vocal tract features such as Mel Frequency Cepstral Coefficients (MFCC) and Dynamic Mel Frequency Cepstral Coefficients (DMFCC) in speaker identification. Feature extraction plays an important role as a front end processing block in Speaker Identification (SI) process. Mel frequency features are used to extract the spectral characteristics o...

This paper proposes the combination multiple facial feature extraction methods and probabilistic neural network for facial recognition. Firstly, we use horizontal projection of 2-D image to obtain accumulated energy profile signal. Secondly, we obtain the statistical distribution of facial gray images. Finally, we adopt wavelet transform to extract low frequency coefficients from 1-D energy pro...

The recent explosion of online streaming services is a reflection of the high importance the multimedia has in our everyday life. These systems deal with large collections of media pieces and their usability is tightly related to the meta-data associated with content. As long as the meta-data is correctly assigned users can easily reach what they were looking for. The presence of poorly annotat...

Herein, we propose a new Markov random field (MRF) image segmentation model which aims at combining color and texture features. The model has a multi-layer structure: Each feature has its own layer, called feature layer, where an MRF model is defined using only the corresponding feature. A special layer is assigned to the combined MRF model. This layer interacts with each feature layer and prov...

In a genetic image object recognition or categorization system, the relevant features or descriptors from a characteristic point, patch or region of an image are often obtained by different approaches. And these features are often separately selected and learned by machine learning methods. In this paper, the relation between distinct features obtained by different feature extraction approaches...

This paper presents an effective method for writer recognition in handwritten documents. We have introduced a set of features that are extracted from two different representations of the contours of handwritten images. These features mainly capture the orientation and curvature information at different levels of observation, first from the chain code sequence of the contours and then from a set...

With an aim of extracting robust facial features under pose variations, this paper presents two directional projections corresponding to extraction of vertical and horizontal local face image features. The matching scores computed from both horizontal and vertical features are subsequently fused at score level via an extreme learning machine that optimizes the total error rate for performance e...

Early recognition and rapid initiation of infection control precautions are currently the most important strategies for controlling severe acute respiratory syndrome (SARS). No rapid diagnostic tests currently exist that can rule out SARS among patients with febrile respiratory illnesses. Clinical features alone cannot with certainty distinguish SARS from other respiratory illnesses rapidly eno...

The paper outlines the work carried out at NTNU as part of the *SEM’13 shared task on Semantic Textual Similarity, using an approach which combines shallow textual, distributional and knowledge-based features by a support vector regression model. Feature sets include (1) aggregated similarity based on named entity recognition with WordNet and Levenshtein distance through the calculation of maxi...

Article history: Received 24 December 2007 Received in revised form 10 April 2008