Face Recognition using Probabilistic Neural Networks

In this paper we address the problem of face detection and recognition of grey scale frontal view images. We propose a face recognition system based on probabilistic neural networks (PNN) architecture. The system is implemented using voronoi/ delaunay tessellations and template matching. Images are segmented successfully into homogeneous regions by virtue of voronoi diagram properties. Face verification is achieved using matching scores computed by correlating edge gradients of reference images. The advantage of classification using PNN models is its short training time. The correlation based template matching guarantees good classification results

Face Recognition using Probabilistic Neural Networks

n this paper we address the problem of face detection and recognition of grey scale frontal view images. We propose a face recognition system based on probabilistic neural networks (PNN) architecture. The system is implemented using voronoi/ delaunay tessellations and template matching. Images are segmented successfully into homogeneous regions by virtue of voronoi diagram properties. Face verification is achieved using matching scores computed by correlating edge gradients of reference images. The advantage of classification using PNN models is its short training time. The correlation based template matching guarantees good classification results.

A Prototype for a Multimodal Biometric Security system based on Face and Audio Signatures

Any automatically measurable, robust and distinctive physical characteristic or personal trait that can be used to identify an individual or verify the claimed identity of an individual, referred to as biometrics, has gained significant interest in the wake of heightened concerns about security and rapid advancements in networking, communication and mobility. Multimodal biometrics is expected to be ultra-secure and reliable, due to the presence of multiple and independent—verification clues. In this study, a multimodal biometric system utilising audio and facial signatures has been implemented and error analysis has been carried out. A total of one thousand face images and 250 sound tracks of 50 users are used for training the proposed system. To account for the attempts of the unregistered signatures data of 25 new users are tested. The short term spectral features were extracted from the sound data and Vector Quantization was done using K-means algorithm. Face images are identified based on Eigen face approach using Principal Component Analysis. The success rate of multimodal system using speech and face is higher when compared to individual unimodal recognition systems

Diversification In Employment Structure And Status Of Rural Women Workers In Ernakulam District

The basic objective of the present study has been to observe the process and pattern of employment diversification among the rural women workers in Ernakulam district. The evidences are that the women workers in the rural areas of the state are being increasingly diversified into the tertiary sector. The clear cut evidence for the fact that in Kerala non-agricultural employment of rural women is increasing with more and more of them getting diversified into the tertiary sector. The women get more self esteem and recognition in terms of the work being done by them. In the urban areas of the state as a poverty eradicating measure the Kerala government has already introduced a new scheme under the banner of Kudumbasree. Another fact noticed in the study that the sectoral shift of women workers has posed a grave problem to the agricultural sector. The reluctance of workers to do manual jobs on land and the prevalence of high wages among the agricultural labours has left many a cultivable area fallow or has induced farmers to shift to less labour –intensive crops. The situation is expected to worsen in future as even the high wages fail to attract the young generation to this sector. To conclude the study has fulfilled all its objectives, viz; highlighting the rural employment structure in Kerala, examining the process, pattern, determinants and consequences of diversification among rural women workers in the sample villages. Being the first of its kind at the micro level in the state it contributes to the available literature in the area enriching the database that is crucially lacking for devising projects at the village and block-level. There exists ample scope for future research of similar nature in an urban background where the secondary data-sources are hinding towards a reversal of trends from non-agriculture to agriculture.

A study of the cost structure of the cashew industry in kerala, karnataka and tamilnadu

Since the world demand for cashew kernels has been rising steadily for several years in the past, conferring significant price increase the processing of cashew remains a highly profitable lndustry. India being the earliest and largest supplier of cashew kernels in the world market it is our prestigious obligations to reestablish her pristine monopoly. Further the added importance ot the indutry in the Socio economic context of the State of Kerala makes various measures impervative in order to bring back to the industry its pristine glory at the late sixties to give a face lift and to stabilize the industry. This present study adopts a comprehensive frame work of analysis compassing the major issues involved in the cultivation, distribution, import, processing and marketing of cashew undcr the private and public sector, migration of the industry and the financial requirements of the industry.

PERFORMANCE OF DIFFERENT CLASSIFIERS IN SPEECH RECOGNITION

Speech is the most natural means of communication among human beings and speech processing and recognition are intensive areas of research for the last five decades. Since speech recognition is a pattern recognition problem, classification is an important part of any speech recognition system. In this work, a speech recognition system is developed for recognizing speaker independent spoken digits in Malayalam. Voice signals are sampled directly from the microphone. The proposed method is implemented for 1000 speakers uttering 10 digits each. Since the speech signals are affected by background noise, the signals are tuned by removing the noise from it using wavelet denoising method based on Soft Thresholding. Here, the features from the signals are extracted using Discrete Wavelet Transforms (DWT) because they are well suitable for processing non-stationary signals like speech. This is due to their multi- resolutional, multi-scale analysis characteristics. Speech recognition is a multiclass classification problem. So, the feature vector set obtained are classified using three classifiers namely, Artificial Neural Networks (ANN), Support Vector Machines (SVM) and Naive Bayes classifiers which are capable of handling multiclasses. During classification stage, the input feature vector data is trained using information relating to known patterns and then they are tested using the test data set. The performances of all these classifiers are evaluated based on recognition accuracy. All the three methods produced good recognition accuracy. DWT and ANN produced a recognition accuracy of 89%, SVM and DWT combination produced an accuracy of 86.6% and Naive Bayes and DWT combination produced an accuracy of 83.5%. ANN is found to be better among the three methods.

Changing Role of Academic Libraries in the E-learning Environment: Issues and Challenges

The development of computer and network technology is changing the education scenario and transforming the teaching and learning process from the traditional physical environment to the digital environment. It is now possible to access vast amount of information online and enable one to one communication without the confines of place or time. While E-learning and teaching is unlikely to replace face-to-face training and education it is becoming an additional delivery method, providing new learning opportunities to many users. It is also causing an impact on library services as the increased use of ICT and web based learning technologies have paved the way for providing new ICT based services and resources to the users. Online learning has a crucial role in user education, information literacy programmes and in training the library professionals. It can help students become active learners, and libraries will have to play a greater role in this process of transformation. The significance of libraries within an institution has improved due to the fact that academic libraries and information services are now responsible for e-learning within their organization.

A Faster 2D Technique for the design of Combinational Digital Circuits Using Genetic Algorithm

Combinational digital circuits can be evolved automatically using Genetic Algorithms (GA). Until recently this technique used linear chromosomes and and one dimensional crossover and mutation operators. In this paper, a new method for representing combinational digital circuits as 2 Dimensional (2D) chromosomes and suitable 2D crossover and mutation techniques has been proposed. By using this method, the convergence speed of GA can be increased significantly compared to the conventional methods. Moreover, the 2D representation and crossover operation provides the designer with better visualization of the evolved circuits. In addition to this, a technique to display automatically the evolved circuits has been developed with the help of MATLAB