This paper presents a multimodal biometric system called “handmetric”, which is the fusion of hand based biometrics including palmprint, knuckleprint and hand shape. Moreover, a new framework of FLF (feature-level fusion) is put forward based on subspace analyzes. While verifies that existing feature concatenating methods are instances of the framework, a parameter optimized model using KPCA (k...

A frequent problem in density level-set estimation is the choice of the right features that give rise to compact and concise representations of the observed data. We present an efficient feature selection method for density level-set estimation where optimal kernel mixing coefficients and model parameters are determined simultaneously. Our approach generalizes one-class support vector machines ...

This paper proposes an efficient technique for partitioning large biometric database during identification. In this technique feature vector which comprises of global and local descriptors extracted from offline signature are used by fuzzy clustering technique to partition the database. As biometric features posses no natural order of sorting, thus it is difficult to index them alphabetically o...

Multimodal biometric systems utilize the evidence presented by multiple biometric sources (e.g., face and fingerprint, multiple fingers of a user, multiple impressions of a single finger, etc.) in order to determine or verify the identity of an individual. Information from multiple sources can be consolidated in three distinct levels [1]: (i) feature extraction level; (ii) match score level; an...

Traditional two-step localization methods and direct have practical problems when they are used for underwater acoustic source localization. In this paper, a method based on the feature-level information fusion is proposed, in which Hough Transform exploited to detect line characteristics of spatial features target. A secondary accumulation procedure proposed extract fuse good instead fusing al...

We studied two methods for the high-level feature extraction (HLF) task: (1) a method based on support vector machines (SVMs) with walk-based graph kernels [1], and (2) a method based on the prefixspan boosting (pboost) algorithm [2]. In the former method, each image is first segmented into a finite set of homogeneous segments and then represented as a segmentation graph where each vertex is a ...

Fingerprint based authentication systems are one of the cost-effective biometric authentication techniques employed for personal identification. As the data base population increases, fast identification/recognition algorithms are required with high accuracy. Accuracy can be increased using multimodal evidences collected by multiple biometric traits. In this work, consecutive fingerprint images...

We present an approach to feature weight optimization for document-level decoding. This is an essential task for enabling future development of discourse-level statistical machine translation, as it allows easy integration of discourse features in the decoding process. We extend the framework of sentence-level feature weight optimization to the document-level. We show experimentally that we can...

In most tasks related to opinion mining and sentiment analysis, it is necessary to compute the semantic orientation (i.e., positive or negative evaluative implications) of certain opinion expressions. Recent works suggest that semantic orientation depends on application domains. Moreover, we think that semantic orientation depends on the specific targets (features) that an opinion is applied to...

Despite the increases in disk capacity and decreases in mechanical delays in recent years, the performance gap between magnetic disks and CPU continues to increase. To improve disk performance, operating systems and file systems must have detailed low-level information (e.g., zoning, bad-sector positions, and cache size) and high-level information (e.g. expected read and write performance for d...