A Study on the Quality Attributes of Kerala as a Global Tourism Destination-2005

The study was carried out with the broad objective to understand the quality attributes of Kerala as a global tourism destination. It also sheds some light on the nature of international travel market for Kerala in terms of activities , benefit sought , country and trip profile. For understanding the difference in level of tourists perception , the study also tried to compare overall trip satisfaction and impression with destination for different tourists groups categorized into country of origin and various socio-demographic groups.

International Initiatives for Regulating Access to Genetic Resources

In light of the various international instruments and international agencies that are actively engaged in resolving the issue of ABS, the present work tries to find an answer to the larger question how far the above agencies have succeeded in regulating access and make sure of benefit sharing. In this process, the work comprehensively analyses the work of different agencies involved in the process. It tries to find out the major obstacles that stand in the way of fulfilment of the benefit sharing objective and proposes the ways and means to tackle them. The study first traces the legal foundations of the concept of property in GRs and associated TK.For this, it starts with analysis of the nature of property and the questions related to ownership in GRs as contained in the CBD as well as in various State legislations. It further examines the notion of property before and after the enactment of the CBD and establishes that the CBD contains strong private property jurisprudence.Based on the theoretical foundation of private property right,Chapter 3 analyses the benefit sharing mechanism of the CBD, i.e. the Nagoya Protocol. It searches for a theoretical convergence of the notion of property as reflected in the two instruments and successfully establishes the same. It makes an appraisal of the Nagoya regime to find out how far it has gone beyond the CBD in ensuring the task of benefit sharing and the impediments in its way.Realizing that the ITPGRFA forms part of the CBD system, Chapter 4 analyses the benefit sharing structure of ITPGRFA as revealed through its multilateral system. This gives the work the benefit of comparing two different benefit sharing models operating on the same philosophy of property. This chapter tries to find out whether there is conceptual coherence in the notion of property when the benefit sharing model changes. It alsocompares the merits and demerits of both the systems and tries to locate the hurdles in achieving benefit sharing. Aware of the legal impediments caused by IPRs in the process of ABS, Chapter 5 tries to explore the linkages between IPRs and GRs and associated TK and assesses why contract-based CBD system fails before the monopoly rights under TRIPS. Chapter 6 analyses the different solutions suggested by the international community at the TRIPS Council as well as the WIPO (World Intellectual property Organisation) and examines their effectiveness. Chapter 7 concludes that considering the inability of the present IP system to understand the grass root realities of the indigenous communities as well as the varying situations of the country of origin, the best possible way to recognise the CBD goals in the TRIPS could be better achieved through linking the two instruments by means of the triple disclosure requirement in Article 29 as suggested by the Disclosure Group during the TRIPS Council deliberations. It also recommends that considering the nature of property in GR, a new section/chapter in the TRIPS dealing with GRs would be another workable solution.

CBIR Using Local and Global Properties of Image Sub-blocks

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 and finding the corner density in each partition. 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). Euclidean distance measure is used for computing the distance between the features 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

Development of Directionally Adaptive Techniques for Single Image Super-Resolution

Super Resolution problem is an inverse problem and refers to the process of producing a High resolution (HR) image, making use of one or more Low Resolution (LR) observations. It includes up sampling the image, thereby, increasing the maximum spatial frequency and removing degradations that arise during the image capture namely aliasing and blurring. The work presented in this thesis is based on learning based single image super-resolution. In learning based super-resolution algorithms, a training set or database of available HR images are used to construct the HR image of an image captured using a LR camera. In the training set, images are stored as patches or coefficients of feature representations like wavelet transform, DCT, etc. Single frame image super-resolution can be used in applications where database of HR images are available. The advantage of this method is that by skilfully creating a database of suitable training images, one can improve the quality of the super-resolved image. A new super resolution method based on wavelet transform is developed and it is better than conventional wavelet transform based methods and standard interpolation methods. Super-resolution techniques based on skewed anisotropic transform called directionlet transform are developed to convert a low resolution image which is of small size into a high resolution image of large size. Super-resolution algorithm not only increases the size, but also reduces the degradations occurred during the process of capturing image. This method outperforms the standard interpolation methods and the wavelet methods, both visually and in terms of SNR values. Artifacts like aliasing and ringing effects are also eliminated in this method. The super-resolution methods are implemented using, both critically sampled and over sampled directionlets. The conventional directionlet transform is computationally complex. Hence lifting scheme is used for implementation of directionlets. The new single image super-resolution method based on lifting scheme reduces computational complexity and thereby reduces computation time. The quality of the super resolved image depends on the type of wavelet basis used. A study is conducted to find the effect of different wavelets on the single image super-resolution method. Finally this new method implemented on grey images is extended to colour images and noisy images

Development of 2-D MRT based Image Compression Techniques

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

Development of N N SMRT for N a power of 2 and its Applications in Image Enhancement

Digital Image Processing is a rapidly evolving eld with growing applications in Science and Engineering. It involves changing the nature of an image in order to either improve its pictorial information for human interpretation or render it more suitable for autonomous machine perception. One of the major areas of image processing for human vision applications is image enhancement. The principal goal of image enhancement is to improve visual quality of an image, typically by taking advantage of the response of human visual system. Image enhancement methods are carried out usually in the pixel domain. Transform domain methods can often provide another way to interpret and understand image contents. A suitable transform, thus selected, should have less computational complexity. Sequency ordered arrangement of unique MRT (Mapped Real Transform) coe cients can give rise to an integer-to-integer transform, named Sequency based unique MRT (SMRT), suitable for image processing applications. The development of the SMRT from UMRT (Unique MRT), forward & inverse SMRT algorithms and the basis functions are introduced. A few properties of the SMRT are explored and its scope in lossless text compression is presented.