31 resultados para Image orientation

em Cochin University of Science


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A series of short-isora-fiber-reinforced natural rubber composites were prepared by the incorporation of fibers of different lengths (6, 10, and 14 mm) at 15 phr loading and at different concentrations (10, 20, 30, and 40 phr) with a 10 mm fiber length. Mixes were also prepared with 10 mm long fibers treated with a 5% NaOH solution. The vulcanization parameters, processability, and stress-strain properties of these composites were analyzed. Properties such as tensile strength, tear strength, and tensile modulus were found to be at maximum for composites containing longitudinally oriented fibers 10 mm in length. Mixes containing fiber loadings of 30 phr with bonding agent (resorcinol-formaldehyde [RF] resin) showed mechanical properties superior to all other composites. Scanning electron microscopy (SEM) studies were carried out to investigate the fiber surface morphology, fiber pullout, and fiber-rubber interface. SEM studies showed that the bonding between the fiber and rubber was improved with treated fibers and with the use of bonding agent.

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International School of Photonics, Cochin University of Science and Technology

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Fourier transform methods are employed heavily in digital signal processing. Discrete Fourier Transform (DFT) is among the most commonly used digital signal transforms. The exponential kernel of the DFT has the properties of symmetry and periodicity. Fast Fourier Transform (FFT) methods for fast DFT computation exploit these kernel properties in different ways. In this thesis, an approach of grouping data on the basis of the corresponding phase of the exponential kernel of the DFT is exploited to introduce a new digital signal transform, named the M-dimensional Real Transform (MRT), for l-D and 2-D signals. The new transform is developed using number theoretic principles as regards its specific features. A few properties of the transform are explored, and an inverse transform presented. A fundamental assumption is that the size of the input signal be even. The transform computation involves only real additions. The MRT is an integer-to-integer transform. There are two kinds of redundancy, complete redundancy & derived redundancy, in MRT. Redundancy is analyzed and removed to arrive at a more compact version called the Unique MRT (UMRT). l-D UMRT is a non-expansive transform for all signal sizes, while the 2-D UMRT is non-expansive for signal sizes that are powers of 2. The 2-D UMRT is applied in image processing applications like image compression and orientation analysis. The MRT & UMRT, being general transforms, will find potential applications in various fields of signal and image processing.

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This thesis studied the impact of market orietnation on business performance, in the seafood industry, which is a unique situation wherein the firms were all 100% export oriented. The study was able to prove that in the context of the seafood indsutry, implementation of market orientation principles will lead to increase in business performance. The business performance variables were measured under two heads, namely economic performance and non-economic performance. Market orientation in Indian seafood firms was significantly and postiively related to both the performance measures. Under the non-economic performance, were the customer and employee consequences.Again market orientation was positively and significantly related to both the consequences.Thus, the implication arising from the study is this: market orientation in Indian seafood processing firms increases their business performance. The implementation of market orientation will help the seafood firms in gaining competitve advantages in exporting. This in turn will result in increased exports and the position of Indian seafood in the global market will be strengthened. It will thus become a leading player in the global fish trade. Next, the focus was on the effect of the antecedents on the market orientation of a firm. It was seen that several factors were antecedents to the adoption of market orientation principles. They include top management emphasis, conflict, centralization and reward system. It is noted that top management emphasis and support is vital to the market orientation programme. The top management needs to adopt market oriented behaviour and reinforce the need for being market oriented, for it to percolate down the line.Interdepartmental conflict is seen to affect market orientation positively. A large percent of the Indian seafood firms are traditionally family-owned companies, rather than professionally managed firms. This would result in promulgation of old ideas of management whereby, conflict was seen as a healthy exercise, which helped to build up each department's efficiency. But, this view in the long run proves to be detrimental to the firm's performance and must therefore be kept to a bare minimum, if any.Decentralisation of decision making facilitates the participation of the lower level employees and builds up their motivational levels and commitment to the firm. Thus employees are encouraged to make their own decisions, so that they can deal with customers faster and more efficiently. Reward systems help improve an employee's morale, provide encouragement and helps inculcate commitment and loyalty. It improves the employee's self worth and fulfills his need for achievement. A satisfied employee works better, produces more output and needs less supervision, and is happy, thereby reducing costs to the company for replacement and retraining, if the employee quits.Competitive intensity plays a moderating role on the market orientation business performance. Thus in times of greater competition, the relationship between market orientation and business performance grows stronger. Thus, this thesis was successful in investigating a positive relationship between business performance and market orientation.

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The small business has attracted very little attention of the historians in the ancient times, or public mind inspite of the fact that its impact on the various civilisations has been phenominal. Even in recent times economists considered the small firms as inappropriate, obselate and anacronistic as it cannot assimilate the full potential of technological change in the production system. But today everybody agrees that the small business has a definite role in shaping the human destiny and enhancing the quality of life in any society. In a developing country like India small firms are necessary to generate employment for millions, high standared of personal choice to consumers, provide competition and act as a check to monopoly power; further the small firms provide an important source of innovation and in turn it paves the way for entrepreneur development in the society. In many countries the small enterprises played a significant role in the growth and development of their economic system. Italy and Japan are quoted as classic examples . In India, too, with the abundance of labour and scarce capital resources small firms have been promoted and protected by the government. But one must say that the small firm owners/managers in India have been shy in developing a market orientation in themeselves. Due to this many firms failed and closed. The alarming rate of sickness among the small firms in India may be attributed to the lack of market driven/customer orientation approach among the owner/managers of small business. So the study on the market oreintation of the small firms has never been in the mind of marketing experts and academicians. Thus, an attempt is made to enquire into them systematically and scientifically. For the study, Trivandrum district in Kerala has been selected. The data for the study has been collected by the help of a schedule which has been prepared after consulting the relevant literature and after consultation with experts in the field, academicians and practising managers.

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This thesis is an outcome of the investigations carried out on the development of an Artificial Neural Network (ANN) model to implement 2-D DFT at high speed. A new definition of 2-D DFT relation is presented. This new definition enables DFT computation organized in stages involving only real addition except at the final stage of computation. The number of stages is always fixed at 4. Two different strategies are proposed. 1) A visual representation of 2-D DFT coefficients. 2) A neural network approach. The visual representation scheme can be used to compute, analyze and manipulate 2D signals such as images in the frequency domain in terms of symbols derived from 2x2 DFT. This, in turn, can be represented in terms of real data. This approach can help analyze signals in the frequency domain even without computing the DFT coefficients. A hierarchical neural network model is developed to implement 2-D DFT. Presently, this model is capable of implementing 2-D DFT for a particular order N such that ((N))4 = 2. The model can be developed into one that can implement the 2-D DFT for any order N upto a set maximum limited by the hardware constraints. The reported method shows a potential in implementing the 2-D DF T in hardware as a VLSI / ASIC

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The present study is on value orientation of professional students•and as such the theoretical value is inherent and implied. Variation on this value is likely to be limited among the subjects. The relevance of the present study is with particular reference, to management as a profession. In organisational settings motivation plays an important role. According to McClelland's theory of needs, achievement, power, and affiliation are the three important needs that help in understanding motivation. Achieve~ent need may be defined as the drive to excel, to achieve in relation to a set of standards, and to strive to succeed. Some people have a compelling drive to succeed. They have a desire to do something better or more efficiently than it has been done before. McClelland found that high achievers differentiate themselves from others by their desire to do things . better. Considering this fact, 'achievement' is included as one of the values for the study

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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

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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

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This paper proposes a region based image retrieval system using the local colour and texture features of image sub regions. The regions of interest (ROI) are roughly identified by segmenting the image into fixed partitions, finding the edge map and applying morphological dilation. The colour and texture features of the ROIs are computed from the histograms of the quantized HSV colour space and Gray Level co- occurrence matrix (GLCM) respectively. Each ROI of the query image is compared with same number of ROIs of the target image that are arranged in the descending order of white pixel density in the regions, using Euclidean distance measure for similarity computation. Preliminary experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods.

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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

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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.

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Development of continuous shrimp cell lines for effective investigation on shrimp viruses remains elusive with an arduous history of over 25 years. Despite presenting challenges to researchers in developing a cell line, the billion dollar aquaculture industry is under viral threat. Advances in molecular biology and various gene transfer technologies for immortalization of cells have resulted in the development of hundreds of cell lines from insects and mammals, but yet not a single cell line has been developed from shrimp and other marine invertebrates. Though improved growth and longevity of shrimp cells in vitro could be achieved by using modified growth media this did not make any leap to spontaneous transformation; probably due to the fact that shrimp cells inhibited neoplastic transformations. Oncogenic induction and immortalization are considered as the possible ways, and an exclusive medium for shrimp cell culture and an appropriate mode of transformation are crucial. In this review status of shrimp cell line development and its future orientation are discussed

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Content Based Image Retrieval is one of the prominent areas in Computer Vision and Image Processing. Recognition of handwritten characters has been a popular area of research for many years and still remains an open problem. The proposed system uses visual image queries for retrieving similar images from database of Malayalam handwritten characters. Local Binary Pattern (LBP) descriptors of the query images are extracted and those features are compared with the features of the images in database for retrieving desired characters. This system with local binary pattern gives excellent retrieval performance

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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