| Abstract: | The objective of the preset work is to develop optical fiber sensors for various physical and chemical parameters. As a part of this we initially investigated trace analysis of silica, ammonia, iron and phosphate in water. For this purpose the author has implemented a dual wavelength probing scheme which has many advantages over conventional evanescent wave sensors. Dual wavelength probing makes the design more reliable and repeatable and this design makes the sensor employable for concentration, chemical content, adulteration level, monitoring and control in industries or any such needy environments. Use of low cost components makes the system cost effective and simple. The Dual wavelength probing scheme is employed for the trace analysis of silica, iron, phosphate, and ammonia in water. Such sensors can be employed for the steam and water quality analysers in power plants. Few samples from a power plant are collected and checked the performance of developed system for practical applications. |
| Description: | Department of Instrumentation, Cochin University of Science and Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/3446 |
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| Dyuthi-T1419.pdf | (5.284Mb) |
| Abstract: | 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 |
| Description: | Department of Electronics Cochin University of Science and Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/3547 |
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| Dyuthi-T1515.pdf | (7.138Mb) |
| Abstract: | The present thesis concentrates largely on sound radiation from floating structure due to moving load |
| Description: | Department Of Ship Technology,Cochin University Of Science And Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/3995 |
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| Dyuthi-T1804.pdf | (5.875Mb) |
| Abstract: | This thesis summarizes the results on the studies on a syntax based approach for translation between Malayalam, one of Dravidian languages and English and also on the development of the major modules in building a prototype machine translation system from Malayalam to English. The development of the system is a pioneering effort in Malayalam language unattempted by previous researchers. The computational models chosen for the system is first of its kind for Malayalam language. An in depth study has been carried out in the design of the computational models and data structures needed for different modules: morphological analyzer , a parser, a syntactic structure transfer module and target language sentence generator required for the prototype system. The generation of list of part of speech tags, chunk tags and the hierarchical dependencies among the chunks required for the translation process also has been done. In the development process, the major goals are: (a) accuracy of translation (b) speed and (c) space. Accuracy-wise, smart tools for handling transfer grammar and translation standards including equivalent words, expressions, phrases and styles in the target language are to be developed. The grammar should be optimized with a view to obtaining a single correct parse and hence a single translated output. Speed-wise, innovative use of corpus analysis, efficient parsing algorithm, design of efficient Data Structure and run-time frequency-based rearrangement of the grammar which substantially reduces the parsing and generation time are required. The space requirement also has to be minimised |
| Description: | Department of Computer Science, Cochin University of Science and Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/3808 |
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| Dyuthi-T1739.pdf | (5.310Mb) |
| Abstract: | The microorganisms are recognized as important sources of protease inhibitors which are valuable in the fields of medicine, agriculture and biotechnology. The protease inhibitors of microbial origin are found to be versatile in their structure and mode of inhibition that vary from those of other sources. Although surplus of low molecular weight non-protein protease inhibitors from microorganisms have been reported, there is a dearth of reports on proteinaceous protease inhibitors. The search for new metabolites from marine organisms has resulted in the isolation of more or less 10,000 metabolites (Fuesetani and Fuesetani, 2000) many of which are gifted with pharmacodynamic properties. The existence of marine microorganisms was reported earlier, and they were found to be metabolically and physiologically dissimilar from terrestrial microorganisms. Marine microorganisms have potential as important new sources of enzyme inhibitors and consequently a detailed study of new marine microbial inhibitors will provide the basis for future research (Imada, 2004). |
| Description: | Department of Biotechnology, Cochin University of Science and Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/3717 |
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| Dyuthi-T1673.pdf | (4.612Mb) |
| Abstract: | One of the main challenges in the development of metal-oxide gas sensors is enhancement of selectivity to a particular gas. Currently, two general approaches exist for enhancing the selective properties of sensors. The first one is aimed at preparing a material that is specifically sensitive to one compound and has low or zero cross-sensitivity to other compounds that may be present in the working atmosphere. To do this, the optimal temperature, doping elements, and their concentrations are investigated. Nonetheless, it is usually very difficult to achieve an absolutely selective metal oxide gas sensor in practice. Another approach is based on the preparation of materials for discrimination between several analyte in a mixture. It is impossible to do this by using one sensor signal. Therefore, it is usually done either by modulation of sensor temperature or by using sensor arrays. The present work focus on the characterization of n-type semiconducting metal oxides like Tungsten oxide (WO3), Zinc Oxide (ZnO) and Indium oxide (In2O3) for the gas sensing purpose. For the purpose of gas sensing thick as well as thin films were fabricated. Two different gases, NO2 and H2S gases were selected in order to study the gas sensing behaviour of these metal oxides. To study the problem associated with selectivity the metal oxides were doped with metals and the gas sensing characteristics were investigated. The present thesis is entitled “Development of semiconductor metal oxide gas sensors for the detection of NO2 and H2S gases” and consists of six chapters. |
| Description: | Department of instrumentation, Cochin University of Science And Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/3481 |
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| Dyuthi-T1475.pdf | (9.295Mb) |
| Abstract: | In this thesis, different techniques for image analysis of high density microarrays have been investigated. Most of the existing image analysis techniques require prior knowledge of image specific parameters and direct user intervention for microarray image quantification. The objective of this research work was to develop of a fully automated image analysis method capable of accurately quantifying the intensity information from high density microarrays images. The method should be robust against noise and contaminations that commonly occur in different stages of microarray development. |
| Description: | Department of Electronics Cochin University of Science and Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/3993 |
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| Dyuthi-T1802.pdf | (17.22Mb) |
| Abstract: | Tellurite glasses are photonic materials of special interest to the branch of optoelectronic and communication, due to its important optical properties such as high refractive index, broad IR transmittance, low phonon energy etc. Tellurite glasses are solutions to the search of potential candidates for nonlinear optical devices. Low phonon energy makes it an efficient host for dopant ions like rare earths, allowing a better environment for radiative transitions. The dopant ions maintain majority of their individual properties in the glass matrix. Tellurites are less toxic than chalcogenides, more chemically and thermally stable which makes them a highly suitable fiber material for nonlinear applications in the midinfrared and they are of increased research interest in applications like laser, amplifier, sensor etc. Low melting point and glass transition temperature helps tellurite glass preparation easier than other glass families. In order to probe into the versatility of tellurite glasses in optoelectronic industry; we have synthesized and undertaken various optical studies on tellurite glasses. We have proved that the highly nonlinear tellurite glasses are suitable candidates in optical limiting, with comparatively lower optical limiting threshold. Tuning the optical properties of glasses is an important factor in the optoelectronic research. We have found that thermal poling is an efficient mechanism in tuning the optical properties of these materials. Another important nonlinear phenomenon found in zinc tellurite glasses is their ability to switch from reverse saturable absorption to saturable absorption in the presence of lanthanide ions. The proposed thesis to be submitted will have seven chapters |
| Description: | International School of Photonics, Cochin University of Science and Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/3558 |
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| Dyuthi-T1540.pdf | (5.846Mb) |
| Abstract: | Tellurite glasses are photonic materials of special interest to the branch of optoelectronic and communication, due to its important optical properties such as high refractive index, broad IR transmittance, low phonon energy etc. Tellurite glasses are solutions to the search of potential candidates for nonlinear optical devices. Low phonon energy makes it an efficient host for dopant ions like rare earths, allowing a better environment for radiative transitions. The dopant ions maintain majority of their individual properties in the glass matrix. Tellurites are less toxic than chalcogenides, more chemically and thermally stable which makes them a highly suitable fiber material for nonlinear applications in the midinfrared and they are of increased research interest in applications like laser, amplifier, sensor etc. Low melting point and glass transition temperature helps tellurite glass preparation easier than other glass families.In order to probe into the versatility of tellurite glasses in optoelectronic industry; we have synthesized and undertaken various optical studies on tellurite glasses. We have proved that the highly nonlinear tellurite glasses are suitable candidates in optical limiting, with comparatively lower optical limiting threshold. Tuning the optical properties of glasses is an important factor in the optoelectronic research. We have found that thermal poling is an efficient mechanism in tuning the optical properties of these materials. Another important nonlinear phenomenon found in zinc tellurite glasses is their ability to switch from reverse saturable absorption to saturable absorption in the presence of lanthanide ions. The proposed thesis to be submitted will have seven chapters. |
| URI: | http://dyuthi.cusat.ac.in/purl/5119 |
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| Dyuthi-T 2184.pdf | (5.843Mb) |
| Abstract: | Knowledge discovery in databases is the non-trivial process of identifying valid, novel potentially useful and ultimately understandable patterns from data. The term Data mining refers to the process which does the exploratory analysis on the data and builds some model on the data. To infer patterns from data, data mining involves different approaches like association rule mining, classification techniques or clustering techniques. Among the many data mining techniques, clustering plays a major role, since it helps to group the related data for assessing properties and drawing conclusions. Most of the clustering algorithms act on a dataset with uniform format, since the similarity or dissimilarity between the data points is a significant factor in finding out the clusters. If a dataset consists of mixed attributes, i.e. a combination of numerical and categorical variables, a preferred approach is to convert different formats into a uniform format. The research study explores the various techniques to convert the mixed data sets to a numerical equivalent, so as to make it equipped for applying the statistical and similar algorithms. The results of clustering mixed category data after conversion to numeric data type have been demonstrated using a crime data set. The thesis also proposes an extension to the well known algorithm for handling mixed data types, to deal with data sets having only categorical data. The proposed conversion has been validated on a data set corresponding to breast cancer. Moreover, another issue with the clustering process is the visualization of output. Different geometric techniques like scatter plot, or projection plots are available, but none of the techniques display the result projecting the whole database but rather demonstrate attribute-pair wise analysis |
| Description: | Department of Computer Science Cochin University of Science and Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/4535 |
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| Dyuthi-T1814.pdf | (3.401Mb) |
| Abstract: | The 20th century witnessed the extensive use of microwaves in industrial, scientific and medical fields. The major hindrance to many developments in the ISM field is the lack of knowledge about the effect of microwaves on materials used in various applications. The study of the interaction of microwaves with materials demanded the knowledge of the dielectric properties of these materials. However, the dielectric properties of many of these materials are still unknown or less studied. This thesis is an effort to shed light into the dielectric properties of some materials which are used in medical, scientific and industrial fields. Microwave phantoms are those materials used in microwave simulation applications. Effort has been taken to develop and characterize low cost, eco-friendly phantoms from Biomaterials and Bioceramics. The interaction of microwaves with living tissues paved way to the development of materials for electromagnetic shielding. Materials with good conductivity/absorption properties could be used for EMI shielding applications. Conducting polymer materials are developed and characterized in this context. The materials which are developed and analyzed in this thesis are Biomaterials, Bioceramics and Conducting polymers. The use of materials of biological origin in scientific and medical applications provides an eco-friendly pathway. The microwave characterization of the materials were done using cavity material perturbation method. Low cost and ecofriendly biomaterial films were developed from Arrowroot and Chitosan. The developed films could be used in applications such as microwave phantom material, capsule material in pharmaceutical applications, trans-dermal patch material and eco-friendly Band-Aids. Bioceramics with better bioresorption and biocompatibility were synthesized. Bioceramics such as Hydroxyapatite, Beta tricalcium phosphate and Biphasic Calcium Phosphate were studied. The prepared bioceramics could be used as phantom material representing Collagen, Bone marrow, Human abdominal wall fat and Human chest fat. Conducting polymers- based on Polyaniline, are developed and characterized. The developed materials can be used in electromagnetic shielding applications such as in anechoic chambers, transmission cables etc |
| Description: | Department of Electronics, Cochin University of Science and Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/4695 |
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| Dyuthi-T1826.pdf | (11.01Mb) |
| Abstract: | The work is intended to study the following important aspects of document image processing and develop new methods. (1) Segmentation ofdocument images using adaptive interval valued neuro-fuzzy method. (2) Improving the segmentation procedure using Simulated Annealing technique. (3) Development of optimized compression algorithms using Genetic Algorithm and parallel Genetic Algorithm (4) Feature extraction of document images (5) Development of IV fuzzy rules. This work also helps for feature extraction and foreground and background identification. The proposed work incorporates Evolutionary and hybrid methods for segmentation and compression of document images. A study of different neural networks used in image processing, the study of developments in the area of fuzzy logic etc is carried out in this work |
| Description: | Dept of Computer Applications Cochin University of Science and Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/3679 |
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| Dyuthi-T1645.pdf | (3.838Mb) |
| Abstract: | Nanoparticulate drug delivery systems provide wide opportunities for solving problems associated with drug stability or disease states and create great expectations in the area of drug delivery (Bosselmann & Williams, 2012). Nanotechnology, in a simple way, explains the technology that deals with one billionth of a meter scale (Ochekpe, et al., 2009). Fewer side effects, poor bioavailability, absorption at intestine, solubility, specific delivery to site of action with good pharmacological efficiency, slow release, degradation of drug and effective therapeutic outcome, are the major challenges faced by most of the drug delivery systems. To a great extent, biopolymer coated drug delivery systems coupled with nanotechnology alleviate the major drawbacks of the common delivery methods. Chitosan, deacetylated chitin, is a copolymer of β-(1, 4) linked glucosamine (deacetylated unit) and N- acetyl glucosamine (acetylated unit) (Radhakumary et al., 2005). Chitosan is biodegradable, non-toxic and bio compatible. Owing to the removal of acetyl moieties that are present in the amine functional groups of chitin, chitosan is readily soluble in aqueous acidic solution. The solubilisation occurs through the protonation of amino groups on the C-2 position of D-glucosamine residues whereby polysaccharide is converted into polycation in acidic media. Chitosan interacts with many active compounds due to the presence of amine group in it. The presence of this active amine group in chitosan was exploited for the interaction with the active molecules in the present study. Nanoparticles of chitosan coupled drugs are utilized for drug delivery in eye, brain, liver, cancer tissues, treatment of spinal cord injury and infections (Sharma et al., 2007; Li, et a., 2009; Paolicelli et al., 2009; Cho et al., 2010). To deliver drugs directly to the intended site of action and to improve pharmacological efficiency by minimizing undesired side effects elsewhere in the body and decrease the long-term use of many drugs, polymeric drug delivery systems can be used (Thatte et al., 2005). |
| Description: | Department of Biotechnology, Cochin University of Science and Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/3714 |
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| Dyuthi-T1671.pdf | (13.68Mb) |
| Abstract: | Magnetic Resonance Imaging (MRI) is a multi sequence medical imaging technique in which stacks of images are acquired with different tissue contrasts. Simultaneous observation and quantitative analysis of normal brain tissues and small abnormalities from these large numbers of different sequences is a great challenge in clinical applications. Multispectral MRI analysis can simplify the job considerably by combining unlimited number of available co-registered sequences in a single suite. However, poor performance of the multispectral system with conventional image classification and segmentation methods makes it inappropriate for clinical analysis. Recent works in multispectral brain MRI analysis attempted to resolve this issue by improved feature extraction approaches, such as transform based methods, fuzzy approaches, algebraic techniques and so forth. Transform based feature extraction methods like Independent Component Analysis (ICA) and its extensions have been effectively used in recent studies to improve the performance of multispectral brain MRI analysis. However, these global transforms were found to be inefficient and inconsistent in identifying less frequently occurred features like small lesions, from large amount of MR data. The present thesis focuses on the improvement in ICA based feature extraction techniques to enhance the performance of multispectral brain MRI analysis. Methods using spectral clustering and wavelet transforms are proposed to resolve the inefficiency of ICA in identifying small abnormalities, and problems due to ICA over-completeness. Effectiveness of the new methods in brain tissue classification and segmentation is confirmed by a detailed quantitative and qualitative analysis with synthetic and clinical, normal and abnormal, data. In comparison to conventional classification techniques, proposed algorithms provide better performance in classification of normal brain tissues and significant small abnormalities. |
| Description: | Department of Computer Applications Cochin University of Science and Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/3692 |
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| Dyuthi-T1658.pdf | (7.902Mb) |
| Abstract: | In the present study, an attempt has been made to prepare composites by incorporating expanded graphite fillers in insulating elastomer matrices and to study its DC electrical conductivity, dielectric properties and electromagnetic shielding characteristics, in addition to evaluating the mechanical properties. Recently, electronic devices and components have been rapidly developing and advancing. Thus, with increased usage of electronic devices, electromagnetic waves generated by electronic systems can potentially create serious problems such as malfunctions of medical apparatus and industry robots and can even cause harm to the human body. Therefore, in this work the applicable utility of the prepared composites as electromagnetic interference (EMI) shielding material are also investigated. The dissertation includes nine chapters |
| Description: | Department of Polymer Science and Rubber Technology,Cochin University Of Science And Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/3416 |
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| Dyuthi T1410.pdf | (7.205Mb) |
| Abstract: | In the current study, epidemiology study is done by means of literature survey in groups identified to be at higher potential for DDIs as well as in other cases to explore patterns of DDIs and the factors affecting them. The structure of the FDA Adverse Event Reporting System (FAERS) database is studied and analyzed in detail to identify issues and challenges in data mining the drug-drug interactions. The necessary pre-processing algorithms are developed based on the analysis and the Apriori algorithm is modified to suit the process. Finally, the modules are integrated into a tool to identify DDIs. The results are compared using standard drug interaction database for validation. 31% of the associations obtained were identified to be new and the match with existing interactions was 69%. This match clearly indicates the validity of the methodology and its applicability to similar databases. Formulation of the results using the generic names expanded the relevance of the results to a global scale. The global applicability helps the health care professionals worldwide to observe caution during various stages of drug administration thus considerably enhancing pharmacovigilance |
| Description: | Department of Computer Applications, Cochin University of Science and Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/4098 |
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| Dyuthi-T1809.pdf | (4.817Mb) |
| Abstract: | Underwater target localization and tracking attracts tremendous research interest due to various impediments to the estimation task caused by the noisy ocean environment. This thesis envisages the implementation of a prototype automated system for underwater target localization, tracking and classification using passive listening buoy systems and target identification techniques. An autonomous three buoy system has been developed and field trials have been conducted successfully. Inaccuracies in the localization results, due to changes in the environmental parameters, measurement errors and theoretical approximations are refined using the Kalman filter approach. Simulation studies have been conducted for the tracking of targets with different scenarios even under maneuvering situations. This system can as well be used for classifying the unknown targets by extracting the features of the noise emanations from the targets. |
| Description: | Department of Electronics, Cochin University of Science and Technology. |
| URI: | http://dyuthi.cusat.ac.in/purl/3928 |
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| Dyuthi-T1789.pdf | (4.814Mb) |
| Abstract: | Image processing has been a challenging and multidisciplinary research area since decades with continuing improvements in its various branches especially Medical Imaging. The healthcare industry was very much benefited with the advances in Image Processing techniques for the efficient management of large volumes of clinical data. The popularity and growth of Image Processing field attracts researchers from many disciplines including Computer Science and Medical Science due to its applicability to the real world. In the meantime, Computer Science is becoming an important driving force for the further development of Medical Sciences. The objective of this study is to make use of the basic concepts in Medical Image Processing and develop methods and tools for clinicians’ assistance. This work is motivated from clinical applications of digital mammograms and placental sonograms, and uses real medical images for proposing a method intended to assist radiologists in the diagnostic process. The study consists of two domains of Pattern recognition, Classification and Content Based Retrieval. Mammogram images of breast cancer patients and placental images are used for this study. Cancer is a disaster to human race. The accuracy in characterizing images using simplified user friendly Computer Aided Diagnosis techniques helps radiologists in detecting cancers at an early stage. Breast cancer which accounts for the major cause of cancer death in women can be fully cured if detected at an early stage. Studies relating to placental characteristics and abnormalities are important in foetal monitoring. The diagnostic variability in sonographic examination of placenta can be overlooked by detailed placental texture analysis by focusing on placental grading. The work aims on early breast cancer detection and placental maturity analysis. This dissertation is a stepping stone in combing various application domains of healthcare and technology. |
| Description: | Department of Computer Applications Cochin University of Science and Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/3892 |
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| Dyuthi-T1784.pdf | (4.406Mb) |
| Abstract: | Cerebral glioma is the most prevalent primary brain tumor, which are classified broadly into low and high grades according to the degree of malignancy. High grade gliomas are highly malignant which possess a poor prognosis, and the patients survive less than eighteen months after diagnosis. Low grade gliomas are slow growing, least malignant and has better response to therapy. To date, histological grading is used as the standard technique for diagnosis, treatment planning and survival prediction. The main objective of this thesis is to propose novel methods for automatic extraction of low and high grade glioma and other brain tissues, grade detection techniques for glioma using conventional magnetic resonance imaging (MRI) modalities and 3D modelling of glioma from segmented tumor slices in order to assess the growth rate of tumors. Two new methods are developed for extracting tumor regions, of which the second method, named as Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA) can also extract white matter and grey matter from T1 FLAIR an T2 weighted images. The methods were validated with manual Ground truth images, which showed promising results. The developed methods were compared with widely used Fuzzy c-means clustering technique and the robustness of the algorithm with respect to noise is also checked for different noise levels. Image texture can provide significant information on the (ab)normality of tissue, and this thesis expands this idea to tumour texture grading and detection. Based on the thresholds of discriminant first order and gray level cooccurrence matrix based second order statistical features three feature sets were formulated and a decision system was developed for grade detection of glioma from conventional T2 weighted MRI modality.The quantitative performance analysis using ROC curve showed 99.03% accuracy for distinguishing between advanced (aggressive) and early stage (non-aggressive) malignant glioma. The developed brain texture analysis techniques can improve the physician’s ability to detect and analyse pathologies leading to a more reliable diagnosis and treatment of disease. The segmented tumors were also used for volumetric modelling of tumors which can provide an idea of the growth rate of tumor; this can be used for assessing response to therapy and patient prognosis. |
| Description: | Department of Electronics Cochin University of Science and Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/3992 |
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| Dyuthi-T1801.pdf | (7.068Mb) |
| Abstract: | The thesis explores the area of still image compression. The image compression techniques can be broadly classified into lossless and lossy compression. The most common lossy compression techniques are based on Transform coding, Vector Quantization and Fractals. Transform coding is the simplest of the above and generally employs reversible transforms like, DCT, DWT, etc. Mapped Real Transform (MRT) is an evolving integer transform, based on real additions alone. The present research work aims at developing new image compression techniques based on MRT. Most of the transform coding techniques employ fixed block size image segmentation, usually 8×8. Hence, a fixed block size transform coding is implemented using MRT and the merits and demerits are analyzed for both 8×8 and 4×4 blocks. The N2 unique MRT coefficients, for each block, are computed using templates. Considering the merits and demerits of fixed block size transform coding techniques, a hybrid form of these techniques is implemented to improve the performance of compression. The performance of the hybrid coder is found to be better compared to the fixed block size coders. Thus, if the block size is made adaptive, the performance can be further improved. In adaptive block size coding, the block size may vary from the size of the image to 2×2. Hence, the computation of MRT using templates is impractical due to memory requirements. So, an adaptive transform coder based on Unique MRT (UMRT), a compact form of MRT, is implemented to get better performance in terms of PSNR and HVS The suitability of MRT in vector quantization of images is then experimented. The UMRT based Classified Vector Quantization (CVQ) is implemented subsequently. The edges in the images are identified and classified by employing a UMRT based criteria. Based on the above experiments, a new technique named “MRT based Adaptive Transform Coder with Classified Vector Quantization (MATC-CVQ)”is developed. Its performance is evaluated and compared against existing techniques. A comparison with standard JPEG & the well-known Shapiro’s Embedded Zero-tree Wavelet (EZW) is done and found that the proposed technique gives better performance for majority of images |
| Description: | Department of Electronics, Cochin University of Science and Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/4740 |
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| Dyuthi-T1838.pdf | (11.99Mb) |
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