Girija Chetty

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Human Gait recognition is one of the most promising research areas at the moment. Gait is the style or manner of walking on foot. Gait recognition aims to identify individuals by the manner in which they walk. Existing Gait representations which capture both motion and appearance information are sensitive to changes in various covariate conditions such as(More)
In this paper we propose a multimodal fusion framework based on novel face-voice fusion techniques for biometric person authentication and liveness verification. Checking liveness guards the system against spoof/replay attacks by ensuring that the biometric data is captured from an authorised live person. The proposed framework based on bi-modal feature(More)
  • Girija Chetty
  • 2009 12th International Conference on Information…
  • 2009
In this paper we propose liveness checking technique for multimodal biometric authentication systems based on audio-visual cross-modal fusion. Liveness checking ensures that biometric cues are acquired from a live person who is actually present at the time of capture for authenticating the identity. The liveness check based on mutual dependency models is(More)
In this paper, we propose novel algorithmic models based on feature transformation in cross-modal subspace and their multimodal fusion for different types of residue features extracted from several intra-frame and inter frame pixel sub-blocks in video sequences for detecting digital video tampering or forgery. An evaluation of proposed residue features(More)
In this paper, a novel digital image watermarking algorithm based on a fast neural network known as Extreme Learning Machine (ELM) for two grayscale images is proposed. The ELM algorithm is very fast and completes its training in milliseconds unlike its other counterparts such as BPN. The proposed watermarking algorithm trains the ELM by using low frequency(More)