Narendra M. Patel

Performance Analysis of Lip Synchronization Using LPC, MFCC and PLP Speech Parameters

Many multimedia applications and entertainment industry products like games, cartoons and film dubbing require speech driven face animation and audio-video synchronization. Only Automatic Speech Recognition system (ASR) does not give good results in noisy environment. Audio Visual Speech Recognition system plays vital role in such harsh environment as it uses both – audio and visual – information. In this paper, we have proposed a novel approach with enhanced performance over traditional methods that have been reported so far. Our algorithm works on the bases of acoustic and visual parameters to achieve better results. We have tested our system for English language using LPC, MFCC and PLP parameters of the speech. Lip parameters like lip width, lip height etc are extracted from the video and these both acoustic and visual parameters are used to train systems like Artificial Neural Network (ANN), Vector Quantization (VQ), Dynamic Time Warping (DTW), Support Vector Machine (SVM). We have employed neural network in our research work with LPC, MFCC and PLP parameters. Results show that our system is giving very good response against tested vowels.

A Composite Trust Model for Secure Routing in Mobile Ad-Hoc Networks

It is imperative to address the issue of secure routing in mobile ad-hoc networks (MANETs) where the nodes seek for cooperative and trusted behaviour from the peer nodes in the absence of well-established infrastructure and centralized authority. Due to the inherent absence of security considerations in the traditional ad-hoc routing protocols, providing security and reliability in the routing of data packets is a major challenge. This work addresses this issue by proposing a composite trust metric based on the concept of social trust and quality-of-service (QoS) trust. Extended from the ad-hoc on-demand distance vector (AODV) routing protocol, we propose an enhanced trustbased model integrated with an attack-pattern discovery mechanism, which attempts to mitigate the adversaries craving to carry out distinct types of packet-forwarding misbehaviours. We present the detailed mode of operations of three distinct adversary models against which the proposed scheme is evaluated. Simulation results under different network conditions depict that the combination of social and QoS trust components provides significant improvement in packet delivery ratio, routing overhead, and energy consumption compared to an existing trust-based scheme.

Template matching and machine learning-based robust facial expression recognition system using multi-level Haar wavelet

ABSTRACT Recognition of facial expressions is important in industrial automation, security, medical, and many other fields. An image is a very rich and high dimensional data structure, which can result into a considerable computation when processed upon directly. Various feature extraction techniques have been proposed to represent the images efficiently in lower dimension which is understandable by the computer. In this paper, we propose Multi-Level Haar wavelet-based approach, which extracts salient features from prominent face regions at two different scales. The approach first segments most informative geometric components such as eye, mouth, etc. using the Adaboost cascade object detector. Segmented components are divided in M × N regions and feature vector is obtained by concatenating local Haar features extracted from each region. Feature vector is projected in Linear Discriminant Analysis space to reduce its size. For classification, we used template matching (Chi-Square and Cosine measure) and machine learning techniques (Logistic Regression and Support Vector Machine). Performance of proposed method is evaluated on various well-known data-sets like CK, Japanese Female Facial Expression, and Taiwanese Facial Expression Image Database. Adaptability of the feature is also tested on in-house Web-Enabled Spontaneous Facial Expression Data-set (WESFED). Comparison with state of the art method shows the superiority of proposed method.