Enhancement of Microwave Properties of Planar Filters and Antennas using Photonic Bandgap (PBG) Structures

In this thesis, we explore the design, computation, and experimental analysis of photonic crystals, with a special emphasis on structures and devices that make a connection with practically realizable systems. First, we analyze the propenies of photonic-crystal: periodic dielectric structures that have a band gap for propagation. The band gap of periodically loaded air column on a dielectric substrate is computed using Eigen solvers in a plane wave basis. Then this idea is extended to planar filters and antennas at microwave regime. The main objectives covered in this thesis are:• Computation of Band Gap origin in Photonic crystal with the abet of Maxwell's equation and Bloch-Floquet's theorem • Extension of Band Gap to Planar structures at microwave regime • Predict the dielectric constant - synthesized dieletric cmstant of the substrates when loaded with Photonic Band Gap (PBG) structures in a microstrip transmission line • Identify the resonant characteristic of the PBG cell and extract the equivalent circuit based on PBG cell and substrate parameters for microstrip transmission line • Miniaturize PBG as Defected Ground Structures (DGS) and use the property to be implemented in planar filters with microstrip transmission line • Extended the band stop effect of PBG / DGS to coplanar waveguide and asymmetric coplanar waveguide. • Formulate design equations for the PBG / DGS filters • Use these PBG / DGS ground plane as ground plane of microstrip antennas • Analysis of filters and antennas using FDID method

Compact dual-band antenna for wireless access point

A compact dual-band printed antenna covering the 2.4 GHz (2400-2485 MHz) and 5.2 GHz (5150-5350 MHz) WLAN bands is presented. The experimental analysis shows a 2:1 VSWR bandwidth of up to 32 and 8% for 2.4 and 5.2 GHz, respectively. The measured radiation patterns are nearly omnidirectional, with moderate gain in both the WLAN bands.

Ultrasound Image Despeckling using Local Binary Pattern Weighted Linear Filtering

Speckle noise formed as a result of the coherent nature of ultrasound imaging affects the lesion detectability. We have proposed a new weighted linear filtering approach using Local Binary Patterns (LBP) for reducing the speckle noise in ultrasound images. The new filter achieves good results in reducing the noise without affecting the image content. The performance of the proposed filter has been compared with some of the commonly used denoising filters. The proposed filter outperforms the existing filters in terms of quantitative analysis and in edge preservation. The experimental analysis is done using various ultrasound images

Hybrid Background Subtraction in Video using Bi-level CodeBook Model

Detection of Objects in Video is a highly demanding area of research. The Background Subtraction Algorithms can yield better results in Foreground Object Detection. This work presents a Hybrid CodeBook based Background Subtraction to extract the foreground ROI from the background. Codebooks are used to store compressed information by demanding lesser memory usage and high speedy processing. This Hybrid method which uses Block-Based and Pixel-Based Codebooks provide efficient detection results; the high speed processing capability of block based background subtraction as well as high Precision Rate of pixel based background subtraction are exploited to yield an efficient Background Subtraction System. The Block stage produces a coarse foreground area, which is then refined by the Pixel stage. The system’s performance is evaluated with different block sizes and with different block descriptors like 2D-DCT, FFT etc. The Experimental analysis based on statistical measurements yields precision, recall, similarity and F measure of the hybrid system as 88.74%, 91.09%, 81.66% and 89.90% respectively, and thus proves the efficiency of the novel system.

Optimization of Lignin Peroxidase, Manganese Peroxidase, and Lac Production from Ganoderma lucidum Under Solid State Fermentation of Pineapple Leaf

This study was undertaken to isolate ligninase-producing white-rot fungi for use in the extraction of fibre from pineapple leaf agriwaste. Fifteen fungal strains were isolated from dead tree trunks and leaf litter. Ligninolytic enzymes (lignin peroxidase (LiP), manganese peroxidase (MnP), and laccase (Lac)), were produced by solid-state fermentation (SSF) using pineapple leaves as the substrate. Of the isolated strains, the one showing maximum production of ligninolytic enzymes was identified to be Ganoderma lucidum by 18S ribotyping. Single parameter optimization and response surface methodology of different process variables were carried out for enzyme production. Incubation period, agitation, and Tween-80 were identified to be the most significant variables through Plackett-Burman design. These variables were further optimized by Box-Behnken design. The overall maximum yield of ligninolytic enzymes was achieved by experimental analysis under these optimal conditions. Quantitative lignin analysis of pineapple leaves by Klason lignin method showed significant degradation of lignin by Ganoderma lucidum under SSF