Finger vein verification has developed a lot since its first proposal, but there is still not a perfect algorithm. It is proved that algorithms with the same overall accuracy may have different misclassified patterns. We could make use of this complementation to fuse individual algorithms together for more precise result. According to our observation, algorithm has different confidence on its d...

Voting is one of important task which has to conduct in a country for electing a government. But being such an important part hence it has to be manage securely and accurately. But the voting percentage decreases year by year because of inflexibility. Most of existing system studied suffers from high FRR rate. In this paper a minutiae based algorithm is used for designing a voting system which ...

In this paper, we introduce a novel algorithm for object tracking in video sequence. In order to represent the object to be tracked, we propose a spatial color histogram model which encodes both the color distribution and spatial information. The object tracking from frame to frame is accomplished via center voting and back projection method. The center voting method has every pixel in the new ...

A new classification algorithm, called VFI5 (for Voting Feature Intervals), is developed and applied to problem of differential diagnosis of erythemato-squamous diseases. The domain contains records of patients with known diagnosis. Given a training set of such records, the VFI5 classifier learns how to differentiate a new case in the domain. VFI5 represents a concept in the form of feature int...

We work with a recently proposed algorithm where an ensemble of base classifiers, combined using weighted majority voting, is used for incremental classification of data. To successfully accommodate novel information without compromising previously acquired knowledge this algorithm requires an adequate strategy to determine the voting weights. Given an instance to classify, we propose to define...

This paper presents a patch-based approach for pose estimation from single images using a kernelized density voting scheme. We introduce a boostinglike algorithm that models the density using a mixture of weighted ‘weak’ estimators. The ‘weak’ density estimators and corresponding weights are learned iteratively from a training set, providing an efficient method for feature selection. Given a qu...

We consider approval voting elections in which each voter votes for a (possibly empty) set of candidates and the outcome consists of a set of k candidates for some parameter k, e.g., committee elections. We are interested in the minimax approval voting rule in which the outcome represents a compromise among the voters, in the sense that the maximum distance between the preference of any voter a...