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 new method for load matching in multimode microwave feating applicators based on the use of dielectric layer superposition

Usage of a dielectric multilayer around a dielectric Sample is studied as a means for improving the efficiency in multimode microwave- heating cavities. The results show that by using additional dielectric constant layers the appearance of undesired reflections at the sample-air interface is avoided and higher power -absorption rates within the sample and high -efficiency designs are obtained

Template assisted fabrication of I-D nanostructures of Nickel,Cobalt, Iron Oxide and Carbon nanotubes and a study on their structural, magnetic and nonlinear optical properties for applications

Department of Physics, Cochin University of Science & Technology

A Sub-block Based Image Retrieval Using Modified Integrated Region Matching.

This paper proposes a content based image retrieval (CBIR) system using the local colour and texture features of selected image sub-blocks and global colour and shape features of the image. The image sub-blocks are roughly identified by segmenting the image into partitions of different configuration, finding the edge density in each partition using edge thresholding, morphological dilation. The colour and texture features of the identified regions are computed from the histograms of the quantized HSV colour space and Gray Level Co- occurrence Matrix (GLCM) respectively. A combined colour and texture feature vector is computed for each region. The shape features are computed from the Edge Histogram Descriptor (EHD). A modified Integrated Region Matching (IRM) algorithm is used for finding the minimum distance between the sub-blocks of the query and target image. Experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods

Template-Assisted Synthesis and Characterization of Passivated Nickel Nanoparticles

Potential applications of nickel nanoparticles demand the synthesis of self-protected nickel nanoparticles by different synthesis techniques. A novel and simple technique for the synthesis of self-protected nickel nanoparticles is realized by the inter-matrix synthesis of nickel nanoparticles by cation exchange reduction in two types of resins. Two different polymer templates namely strongly acidic cation exchange resins and weakly acidic cation exchange resins provided with cation exchange sites which can anchor metal cations by the ion exchange process are used. The nickel ions which are held at the cation exchange sites by ion fixation can be subsequently reduced to metal nanoparticles by using sodium borohydride as the reducing agent. The composites are cycled repeating the loading reduction cycle involved in the synthesis procedure. X-Ray Diffraction, Scanning Electron Microscopy, Transmission Electron microscopy, Energy Dispersive Spectrum, and Inductively Coupled Plasma Analysis are effectively utilized to investigate the different structural characteristics of the nanocomposites. The hysteresis loop parameters namely saturation magnetization and coercivity are measured using Vibrating Sample Magnetometer. The thermomagnetization study is also conducted to evaluate the Curie temperature values of the composites. The effect of cycling on the structural and magnetic characteristics of the two composites are dealt in detail. A comparison between the different characteristics of the two nanocomposites is also provided

Multifinger Feature Level Fusion Based Fingerprint Identification

Fingerprint based authentication systems are one of the cost-effective biometric authentication techniques employed for personal identification. As the data base population increases, fast identification/recognition algorithms are required with high accuracy. Accuracy can be increased using multimodal evidences collected by multiple biometric traits. In this work, consecutive fingerprint images are taken, global singularities are located using directional field strength and their local orientation vector is formulated with respect to the base line of the finger. Feature level fusion is carried out and a 32 element feature template is obtained. A matching score is formulated for the identification and 100% accuracy was obtained for a database of 300 persons. The polygonal feature vector helps to reduce the size of the feature database from the present 70-100 minutiae features to just 32 features and also a lower matching threshold can be fixed compared to single finger based identification