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

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.

Global Value Chain Linkages of Manufacturing Export Firms: A Study of The Kannur Home Textile Industry

The literature on the involvement of developing countries in trade has focused on the effects of different aspects of globalization on firms, regions and countries. The study attempts to examine how an export based industry, locallyembedded and originated on the basis of regional strengths has been inserted into the global trade framework. Though the unit of analysis is the manufacturing export firm in the region of Kannur, it represents the entire home textile export industry from the state of Kerala, as close to 90% of fabric exports in home furnishing material, textiles for upholstery and decoration and stitched or fused, and branded made ups are from the region. From a global perspective, how developing countries face newer trade restrictions and overcome non quota barriers by firm and region specific activities within a value chain framework is a major research area, which has already contributions from the Ludhiana woolen cluster (Tewari,1999 ) and the Tirupur cluster in India (Cawthorne, 1995). The study contributes to the value chain literature by examining the governance and upgrading as well as how firms benefit from linkages. India has a number of export oriented agglomerations or regions where firms have been serving export markets for many years. In many cases it is no longer the supply side policy actions that determine how they are able to penetrate new markets or expand existing market share. Based on this study it becomes possible to understand how the global value chain operates in these different industries to examine whether there is a danger of immiserisation of growth or low road growth

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

Image Denoising Using Sure-Based Adaptive Thresholding In Directionlet Domain

The standard separable two dimensional wavelet transform has achieved a great success in image denoising applications due to its sparse representation of images. However it fails to capture efficiently the anisotropic geometric structures like edges and contours in images as they intersect too many wavelet basis functions and lead to a non-sparse representation. In this paper a novel de-noising scheme based on multi directional and anisotropic wavelet transform called directionlet is presented. The image denoising in wavelet domain has been extended to the directionlet domain to make the image features to concentrate on fewer coefficients so that more effective thresholding is possible. The image is first segmented and the dominant direction of each segment is identified to make a directional map. Then according to the directional map, the directionlet transform is taken along the dominant direction of the selected segment. The decomposed images with directional energy are used for scale dependent subband adaptive optimal threshold computation based on SURE risk. This threshold is then applied to the sub-bands except the LLL subband. The threshold corrected sub-bands with the unprocessed first sub-band (LLL) are given as input to the inverse directionlet algorithm for getting the de-noised image. Experimental results show that the proposed method outperforms the standard wavelet-based denoising methods in terms of numeric and visual quality

Fishery Commodity Chain Trap vis-à-vis Global Quality Standards: An Analysis of the Kerala Marine Fishery

The article examines the commodity chain trap of marine fishery in Kerala, at both material and value terms, and its ramifications in the globalised fishery chains. The marketing chains both material and value, are very complex in nature since they involve many types of markets and large number of intermediaries and participants. The article also scrutinizes the sensitivity of consumers’ and country’s responses in terms of dietary and hygienic standards relating to seafood trade. In addition, it discusses the devastating effect about the recent stipulations like the US Bio- Terrorism Act and Shrimp anti-dumping duty on the Kerala fishery products