In this paper, we proposed a new fingerprint matching algorithm based on local geometric feature of fingerprint minutia and texture feature for each minutia. To describe the geometric feature of fingerprint minutia, we build a bi-minutia based bar model and get the geometric relationship between the bar and ridges of two candidate minutia; to demonstrate the texture feature, we creatively adopt...

A combination of several classifiers using global features for the content description of medical images is proposed. Beside well known texture histogram features, downscaled representations of the original images are used, which preserve spatial information and utilize distance measures which are robust regarding common variations in radiation dose, translation, and local deformation. These fe...

Gabor wavelet-based feature extraction has been emerging as one of the most promising ways to represent human face image data. In this paper, we examine the performance of two types of classifiers that can be used with Gabor features. In the first classifier, the distance between two images is computed by summing the local distances among all the nodes. In the second classifier, a voting strate...

In many research fields such as Psychology, Linguistics, Cognitive Science and Artificial Intelligence, computing semantic similarity between words is an important issue. In this paper a new semantic similarity metric, that exploits some notions of the feature based theory of similarity and translates it into the information theoretic domain, which leverages the notion of Information Content (I...

This article deals with image and video segmentation using active contours. The proposed variational approachs is based on a criterion combining geometric prior and statistical features computed on the inside region of the contours. The geometric prior involves a free form deformation from a reference contour as opposed to a parametric transformation. Differentiation of this geometric prior cri...

We propose an efficient approach for tracking humans in presence of severe occlusions through a combination of edge and color features. We implement a part based tracking paradigm to localize, accurately, the head, torso and the legs of a human target in successive frames. The Non-parametric color probability density estimates of these parts of the target are used to track them independently us...

The success of supervised learning approaches to word sense disambiguation is largely dependent on the features used to represent the context in which an ambiguous word occurs. Previous work has reached mixed conclusions; some suggest that combinations of syntactic and lexical features will perform most effectively. However, others have shown that simple lexical features perform well on their o...

In this paper, we propose a novel system to analyze vigilance level combining both video and Electrooculography (EOG) features. For one thing, the video features extracted from an infrared camera include percentage of closure (PERCLOS) and eye blinks, slow eye movement (SEM), rapid eye movement (REM) are also extracted from EOG signals. For another, other features like yawn frequency, body post...

A combination of several classifiers using global features for the content description of medical images is proposed. Beside well known texture histogram features, downscaled representations of the original images are used, which preserve spatial information and utilize distance measures which are robust with regard to common variations in radiation dose, translation, and local deformation. The...

We present an action recognition and detection system from temporally untrimmed videos by combining motion and appearance features. Motion and appearance are two kinds of complementary cues for human action understanding from video. For motion features, we adopt the Fisher vector representation with improved dense trajectories due to its rich descriptive capacity. For appearance feature, we cho...