Unsharpmaskingusingquadratic filterfortheenhancement of fingerprintsinnoisybackground

The papersummarizesthedesignandimplementationofaquadraticedgedetection filter basedon Volterraseries.The filter isemployedinanunsharpmaskingschemeforenhancing fingerprints inadark and noisybackground.Theproposed filter canaccountformuchofthepolynomialnonlinearities inherent intheinputimageandcanreplacetheconventionaledgedetectorslikeLaplacian,LoG,etc.The application ofthenew filter isinforensicinvestigationwhereenhancementandidentification oflatent fingerprints arekeyissues.Theenhancementofimagesbytheproposedmethodissuperiortothatwith unsharp maskingschemeemployingconventional filters intermsofthevisualquality,thenoise performance and the computational complexity,making it an ideal candidate for latent fingerprint enhancement.

Development of a Biometric Personal Authentication System Based on Fingerprint and Speech

Biometrics deals with the physiological and behavioral characteristics of an individual to establish identity. Fingerprint based authentication is the most advanced biometric authentication technology. The minutiae based fingerprint identification method offer reasonable identification rate. The feature minutiae map consists of about 70-100 minutia points and matching accuracy is dropping down while the size of database is growing up. Hence it is inevitable to make the size of the fingerprint feature code to be as smaller as possible so that identification may be much easier. In this research, a novel global singularity based fingerprint representation is proposed. Fingerprint baseline, which is the line between distal and intermediate phalangeal joint line in the fingerprint, is taken as the reference line. A polygon is formed with the singularities and the fingerprint baseline. The feature vectors are the polygonal angle, sides, area, type and the ridge counts in between the singularities. 100% recognition rate is achieved in this method. The method is compared with the conventional minutiae based recognition method in terms of computation time, receiver operator characteristics (ROC) and the feature vector length. Speech is a behavioural biometric modality and can be used for identification of a speaker. In this work, MFCC of text dependant speeches are computed and clustered using k-means algorithm. A backpropagation based Artificial Neural Network is trained to identify the clustered speech code. The performance of the neural network classifier is compared with the VQ based Euclidean minimum classifier. Biometric systems that use a single modality are usually affected by problems like noisy sensor data, non-universality and/or lack of distinctiveness of the biometric trait, unacceptable error rates, and spoof attacks. Multifinger feature level fusion based fingerprint recognition is developed and the performances are measured in terms of the ROC curve. Score level fusion of fingerprint and speech based recognition system is done and 100% accuracy is achieved for a considerable range of matching threshold

An Improved Technique for Evolving Wavelet Coefficients for Fingerprint Image Compression

In this paper, an improved technique for evolving wavelet coefficients refined for compression and reconstruction of fingerprint images is presented. The FBI fingerprint compression standard [1, 2] uses the cdf 9/7 wavelet filter coefficients. Lifting scheme is an efficient way to represent classical wavelets with fewer filter coefficients [3, 4]. Here Genetic algorithm (GA) is used to evolve better lifting filter coefficients for cdf 9/7 wavelet to compress and reconstruct fingerprint images with better quality. Since the lifting filter coefficients are few in numbers compared to the corresponding classical wavelet filter coefficients, they are evolved at a faster rate using GA. A better reconstructed image quality in terms of Peak-Signal-to-Noise-Ratio (PSNR) is achieved with the best lifting filter coefficients evolved for a compression ratio 16:1. These evolved coefficients perform well for other compression ratios also.

Faster techniques to evolve wavelet coefficients for better fingerprint image compression

In this article, techniques have been presented for faster evolution of wavelet lifting coefficients for fingerprint image compression (FIC). In addition to increasing the computational speed by 81.35%, the coefficients performed much better than the reported coefficients in literature. Generally, full-size images are used for evolving wavelet coefficients, which is time consuming. To overcome this, in this work, wavelets were evolved with resized, cropped, resized-average and cropped-average images. On comparing the peak- signal-to-noise-ratios (PSNR) offered by the evolved wavelets, it was found that the cropped images excelled the resized images and is in par with the results reported till date. Wavelet lifting coefficients evolved from an average of four 256 256 centre-cropped images took less than 1/5th the evolution time reported in literature. It produced an improvement of 1.009 dB in average PSNR. Improvement in average PSNR was observed for other compression ratios (CR) and degraded images as well. The proposed technique gave better PSNR for various bit rates, with set partitioning in hierarchical trees (SPIHT) coder. These coefficients performed well with other fingerprint databases as well.

Evolution of Better Wavelet Coefficients for Fingerprint Image Compression using cropped images

This paper explains the Genetic Algorithm (GA) evolution of optimized wavelet that surpass the cdf9/7 wavelet for fingerprint compression and reconstruction. Optimized wavelets have already been evolved in previous works in the literature, but they are highly computationally complex and time consuming. Therefore, in this work, a simple approach is made to reduce the computational complexity of the evolution algorithm. A training image set comprised of three 32x32 size cropped images performed much better than the reported coefficients in literature. An average improvement of 1.0059 dB in PSNR above the classical cdf9/7 wavelet over the 80 fingerprint images was achieved. In addition, the computational speed was increased by 90.18 %. The evolved coefficients for compression ratio (CR) 16:1 yielded better average PSNR for other CRs also. Improvement in average PSNR was experienced for degraded and noisy images as well

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

AN INVESTIGATION ON AIR-SEA INTERACTION IN THE INDIAN OCEAN DURING CONTRASTING MONSOONS

The study is undertaken with an objective to investigate the linkage between air-sea fluxes in the Indian Ocean and monsoon forcing. Since the monsoon activity is linked to fluxes, the variability of surface marine meteorological fields under the variable monsoon conditions is also studied. The very objective of the present study is to document various sea surface parameters of the Indian Ocean and to examine the anomalies found in them. Hence it is attempted to relate the anomaly to the variability of monsoon over India, highlighting the occasion of contrasting monsoon periods. The analysis of anomalies of surface meteorological fields such as SST, wind speed and direction, sea level pressure and cloud cover for contrasting monsoons are also studied. During good monsoon years, the pressure anomalies are negative indicating a fall in SLP during pre-monsoon and monsoon months. The interaction of the marine atmosphere with tropical Indian Ocean and its influence on ISMR continue to be an area of active research.

Diblock and Triblock Copolymers of Styrene and Acetoxymethylstyrene by One-Pot ATRP

We describe the synthesis of diblock and triblock copolymers by sequential atom transfer radical polymerization of styrene and acetoxymethylstyrene. Contrary to the usual block copolymerization involving isolation of the macroinitiator, a convenient one-pot procedure is developed. This is possible because of the preferential polymerization of acetoxymethylstyrene, even in the presence of residual styrene, as inferred from characterization of the intermediate polystyrenes and the block copolymers by size exclusion chromatography, 1H NMR, Fourier transform infrared spectroscopy, differential scanning calorimetry, and GPEC techniques. The latent acetoxy functionalities in these block copolymers are shown to be easily unmasked to OOH and OBr functionalities, with the potential for block ionomers and dense graft architectures.

Development of a Technique for Estimating Rain Parameters from Rain Noise Measurements

The measurement of global precipitation is of great importance in climate modeling since the release of latent heat associated with tropical convection is one of the pricipal driving mechanisms of atmospheric circulation.Knowledge of the larger-scale precipitation field also has important potential applications in the generation of initial conditions for numerical weather prediction models Knowledge of the relationship between rainfall intensity and kinetic energy, and its variations in time and space is important for erosion prediction. Vegetation on earth also greatly depends on the total amount of rainfall as well as the drop size distribution (DSD) in rainfall.While methods using visible,infrared, and microwave radiometer data have been shown to yield useful estimates of precipitation, validation of these products for the open ocean has been hampered by the limited amount of surface rainfall measurements available for accurate assessement, especially for the tropical oceans.Surface rain fall measurements(often called the ground truth)are carried out by rain gauges working on various principles like weighing type,tipping bucket,capacitive type and so on.The acoustic technique is yet another promising method of rain parameter measurement that has many advantages. The basic principle of acoustic method is that the droplets falling in water produce underwater sound with distinct features, using which the rainfall parameters can be computed. The acoustic technique can also be used for developing a low cost and accurate device for automatic measurement of rainfall rate and kinetic energy of rain.especially suitable for telemetry applications. This technique can also be utilized to develop a low cost Disdrometer that finds application in rainfall analysis as well as in calibration of nozzles and sprinklers. This thesis is divided into the following 7 chapters, which describes the methodology adopted, the results obtained and the conclusions arrived at.

Sea Surface Temperature-Convection Relationship in Tropical Oceans with Special Emphasis to Intraseasonal Variability of Indian Summer Monsoon

The SST convection relation over tropical ocean and its impact on the South Asian monsoon is the first part of this thesis. Understanding the complicated relation between SST and convection is important for better prediction of the variability of the Indian monsoon in subseasonal, seasonal, interannual, and longer time scales. Improved global data sets from satellite scatterometer observations of SST, precipitation and refined reanalysis of global wind fields have made it possible to do a comprehensive study of the SST convection relation. Interaction of the monsoon and Indian ocean has been discussed. A coupled feedback process between SST and the Active-Break cycle of the Asian summer monsoon is a central theme of the thesis. The relation between SST and convection is very important in the field of numerical modeling of tropical rainfall. It is well known that models generally do very well simulating rainfall in areas of tropical convergence zones but are found unable to do satisfactory simulation in the monsoon areas. Thus in this study we critically examined the different mechanisms of generation of deep convection over these two distinct regions.The study reported in chapter 3 has shown that SST - convection relation over the warm pool regions of Indian and west Pacific oceans (monsoon areas) is in such a way that convection increases with SST in the SST range 26-29 C and for SST higher than 29-30 C convection decreases with increase of SST (it is called Waliser type). It is found that convection is induced in areas with SST gradients in the warm pool areas of Indian and west Pacific oceans. Once deep convection is initiated in the south of the warmest region of warm pool, the deep tropospheric heating by the latent heat released in the convective clouds produces strong low level wind fields (Low level Jet - LLJ) on the equatorward side of the warm pool and both the convection and wind are found to grow through a positive feedback process. Thus SST through its gradient acts only as an initiator of convection. The central region of the warm pool has very small SST gradients and large values of convection are associated with the cyclonic vorticity of the LLJ in the atmospheric boundary layer. The conditionally unstable atmosphere in the tropics is favorable for the production of deep convective clouds.

Biochemical and molecular investigations on Salmonella serovars from seafood

The present investigation was envisaged to determine the prevalence and identify the different Salmonella serovar in seafood from Cochin area. Though, the distribution of Salmonella serovars in different seafood samples of Cochin has been well documented, the present attempt was made to identify the different Salmonella serovars and determine its prevalence in various seafoods. First pan of this investigation involved the isolation and identification of Salmonella strains with the help of different conventional culture methods. The identified isolates were used for the further investigation i.e. serotyping, this provides the information about the prevalent serovars in seafood. The prevalent Salmonella strains have been further characterized based on the utilization of different sugars and amino acids, to identify the different biovar of a serovar.A major research gap was observed in molecular characterization of Salmonella in seafood. Though, previous investigations reported the large number of Salmonella serovars from food sources in India, yet, very few work has been reported regarding genetic characterization of Salmonella serovars associated with food. Second part of this thesis deals with different molecular fingerprint profiles of the Salmonella serovars from seafood. Various molecular typing methods such as plasmid profiling, characterization of virulence genes, PFGE, PCR- ribotyping, and ERIC—PCR have been used for the genetic characterization of Salmonella serovars.The conventional culture methods are mainly used for the identification of Salmonella in seafood and most of the investigations from India and abroad showed the usage of culture method for detection of Salmonella in seafood. Hence, development of indigenous, rapid molecular method is most desirable for screening of Salmonella in large number of seafood samples at a shorter time period. Final part of this study attempted to develop alternative, rapid molecular detection method for the detection of Salmonella in seafood. Rapid eight—hour PCR assay has been developed for detection of Salmonella in seafood. The performance of three different methods viz., culture, ELISA and PCR assays were evaluated for detection of Salmonella in seafood and the results were statistically analyzed. Presence of Salmonella cells in food and enviromnental has been reported low in number, hence, more sensitive method for enumeration of Salmonella in food sample need to be developed. A quantitative realtime PCR has been developed for detection of Salmonella in seafood. This method would be useful for quantitative detection of Salmonella in seafood.

Nutrient Mobility in Chalakudy River,Typified With Riparian Buffer Zone and Its Adjoining Estuary:Spatiotemporal Manifestation

This study was aimed at to characterize the spatio-temporal trends in the distributional characteristics of various species of nitrogen and phosphorus as well as to elucidate the factors and processes aflecting these nutrients in the dissolved, particulate and sedimentary phases of a river estuarine system. The main area of study is Chalakudy river in Kerala, which is a fresh water system originating from Anamalai hills and ending at Arabian Sea. Its basin is between I00 05 ’ to I00 35’ North latitude and 76” 15 ’ to 760 55’ East longitude. Being a riparian bufler zone, the dynamics of nutrient mobility tend to be more complex and variable in this river-estuarine system.The diflerent species of nitrogen estimated from the filtrate were nitrite-N, nitrateN, ammonia-N, urea-N, total nitrogen and residual nitrogen. The diflerent forms of phosphorus estimated from the filtrate were phosphate-P, total-P and residualP. Pre weighed sediments as well as particulate matter were analysed for quantijying nitrite-N, nitrate-N, ammonia-N and urea-N. Total nitrogen was estimated after digestion with potassium persulfate. Fractionation of phosphorus in sediment/particulate matter was performed by applying sequential extraction procedure. The dijferent forms of phosphorus thus estimated were loosely bound (exchangeable) P, Fe/Al bound P, polyphosphates, Ca bound P and refractory P. Sedimental total P was also measured directly by applying digestion method.The analyses carried out in this bimonthly annual survey have revealed specific information on the latent factors influencing the water quality pattern ofthe river. There was dependence among the chemical components of the river sediment and suspended matter, reflecting the water quality. A period of profound environmental change occurred and changes in various species had been noted in association with seasonal variations in the waterway, especially following enhanced river runoff during the monsoon. The results also successfully represented the distribution trend of nutrients during the rainy as well as dry season. Thus, the information gathered in this work will also be beneficial for those interested or involved in river management, conservation, regulation and policy making in regional and national levels.

Development of solar air heaters & thermal energy storage system for drying applications in food processing industries

In the present work, the author has designed and developed all types of solar air heaters called porous and nonporous collectors. The developed solar air heaters were subjected to different air mass flow rates in order to standardize the flow per unit area of the collector. Much attention was given to investigate the performance of the solar air heaters fitted with baffles. The output obtained from the experiments on pilot models, helped the installation of solar air heating system for industrial drying applications also. Apart from these, various types of solar dryers, for small and medium scale drying applications, were also built up. The feasibility of ‘latent heat thermal energy storage system’ based on Phase Change Material was also undertaken. The application of solar greenhouse for drying industrial effluent was analyzed in the present study and a solar greenhouse was developed. The effectiveness of Computational Fluid Dynamics (CFD) in the field of solar air heaters was also analyzed. The thesis is divided into eight chapters.