Palmprint verification is an important tool for authentication of an individual and it can be of significant value in security and ecommerce applications. Palmprint identification has gained high impact over the other biometric modalities due to its reliability and high user acceptance. This paper presents a palmprint based identification approach which uses the Gabor wavelet to extract multipl...

In this paper we adapt an AdaBoost-based image processing algorithm to the task of predicting whether an audio signal contains speech or music. We derive a frame-level discriminator that is both fast and accurate. Using a simple FFT and no built-in prior knowledge of signal structure we obtain an accuracy of 88% on frames sampled at 20ms intervals. When we smooth the output of the classifier wi...

The performance of many computer vision methods depends on the quality of the local features extracted from the images. For most methods the local features are extracted independently of the task and they remain constant through the whole process. To make features more dynamic and give models a choice in the features they can use, this work introduces a set of intermediate features referred as ...

This paper presents a feature level fusion approach which uses the improved K-medoids clustering algorithm and isomorphic graph for face and palmprint biometrics. Partitioning around medoids (PAM) algorithm is used to partition the set of n invariant feature points of the face and palmprint images into k clusters. By partitioning face and palmprint images with scale invariant features SIFT poin...

A feature-level fusion approach is proposed for improving the efficiency of palmprint identification. Multiple Gabor filters are employed to extract the phase information on a palmprint image, which is then merged according to a fusion rule to produce a single feature called the Fusion Code. The similarity of two Fusion Codes is measured by their normalized hamming distance. A database containi...

 A_CL1_1: choose the best-performing classifier for each concept from all the following runs and an event detection method.  A_CL2_2: (visual-based) choose the best-performing visual-based classifier for each concept from runs A_CL4_4, A_CL5_5, and A_CL6_6.  A_CL3_3: (visual-text) weighted average fusion of visual-based classifier A_CL4_4 with a text classifier.  A_CL4_4: (visual-based) ave...

We briefly review the various models proposed for data fusion systems. A common theme of these models is the existence of multiple levels of processing within the data fusion process. We highlight some of the issues which emerge from using such a layered approach, in particular the selection of sources at each level which are both relevant and complementary. The balance between relevance and co...

Until now, of highest relevance for remote sensing data processing and analysis have been techniques for pixel level image fusion. So, This paper attempts to undertake the study of Feature-Level based image fusion. For this purpose, feature based fusion techniques, which are usually based on empirical or heuristic rules, are employed. Hence, in this paper we consider feature extraction (FE) for...

In this paper, we propose a feature-level fusion approach for improving the efficiency of palmprint identification. Multiple elliptical Gabor filters with different orientations are employed to extract the phase information on a palmprint image, which is then merged according to a fusion rule to produce a single feature called the Fusion Code. The similarity of two Fusion Codes is measured by t...

The biometric authentication is an efficient alternative for conventional authentication techniques. Researches in this field show that multi-model biometric systems perform better than single mode. The basic idea of multi-model biometrics is the integration (fusion) of the various biometric mode data. Information from multiple sources can be integrated at three distinct levels: (i) feature ext...