most citedOffline Signature Identification by Fusion of Multiple Classifiers using Statistical Learning Theory

34 citations · 37 across the 9 of their papers we have counts for

collaborators
Showing cs.CVShow all

9 papers · 1 filter

cs.CV2010

Ear Identification by Fusion of Segmented Slice Regions using Invariant Features: An Experimental Manifold with Dual Fusion Approach

Dakshina Ranjan Kisku, Phalguni Gupta, Jamuna Kanta Sing

This paper proposes a robust ear identification system which is developed by fusing SIFT features of color segmented slice regions of an ear. The proposed ear identification method…

cs.CV2010

Feature Level Fusion of Face and Palmprint Biometrics by Isomorphic Graph-based Improved K-Medoids Partitioning

Dakshina Ranjan Kisku, Phalguni Gupta, Jamuna Kanta Sing

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 arou…

cs.CV201034 cited

Offline Signature Identification by Fusion of Multiple Classifiers using Statistical Learning Theory

Dakshina Ranjan Kisku, Phalguni Gupta, Jamuna Kanta Sing

This paper uses Support Vector Machines (SVM) to fuse multiple classifiers for an offline signature system. From the signature images, global and local features are extracted and t…

cs.CV2010

Robust multi-camera view face recognition

Dakshina Ranjan Kisku, Hunny Mehrotra, Phalguni Gupta +1

This paper presents multi-appearance fusion of Principal Component Analysis (PCA) and generalization of Linear Discriminant Analysis (LDA) for multi-camera view offline face recogn…

cs.CV2010

Multibiometrics Belief Fusion

Dakshina Ranjan Kisku, Jamuna Kanta Sing, Phalguni Gupta

This paper proposes a multimodal biometric system through Gaussian Mixture Model (GMM) for face and ear biometrics with belief fusion of the estimated scores characterized by Gabor…

cs.CV20101 cited

Fusion of Multiple Matchers using SVM for Offline Signature Identification

Dakshina Ranjan Kisku, Phalguni Gupta, Jamuna Kanta Sing

This paper uses Support Vector Machines (SVM) to fuse multiple classifiers for an offline signature system. From the signature images, global and local features are extracted and t…