17 resultados para tranquil scene

em Indian Institute of Science - Bangalore - Índia


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Modern science, which was an indigenous product of Western culture, is now being practised in many non-Western countries. This paper discusses the peculiar social, cultural and intellectual problems which scientists of these non-Western countries face in adopting Western science in their situations, with special reference to India. It is pointed out that, in addition to money and communication, it is necessary to have a proper psychological gestalt to practise science satisfactorily. The author analyzes his experience as a physics student in India and in the United States to clarify the nature of this psychological gestalt, and to explain what makes it difficult for non-Western scientists to acquire it.

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Biotechnology holds great promise, and is sure to make an impact in India in the nineties. The role of the government's Department of Biotechnology in focusing attention and resources on crucial problems and in supporting basic research is laudable.

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This paper describes a new method of color text localization from generic scene images containing text of different scripts and with arbitrary orientations. A representative set of colors is first identified using the edge information to initiate an unsupervised clustering algorithm. Text components are identified from each color layer using a combination of a support vector machine and a neural network classifier trained on a set of low-level features derived from the geometric, boundary, stroke and gradient information. Experiments on camera-captured images that contain variable fonts, size, color, irregular layout, non-uniform illumination and multiple scripts illustrate the robustness of the method. The proposed method yields precision and recall of 0.8 and 0.86 respectively on a database of 100 images. The method is also compared with others in the literature using the ICDAR 2003 robust reading competition dataset.

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In this paper, we describe a method for feature extraction and classification of characters manually isolated from scene or natural images. Characters in a scene image may be affected by low resolution, uneven illumination or occlusion. We propose a novel method to perform binarization on gray scale images by minimizing energy functional. Discrete Cosine Transform and Angular Radial Transform are used to extract the features from characters after normalization for scale and translation. We have evaluated our method on the complete test set of Chars74k dataset for English and Kannada scripts consisting of handwritten and synthesized characters, as well as characters extracted from camera captured images. We utilize only synthesized and handwritten characters from this dataset as training set. Nearest neighbor classification is used in our experiments.

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In this paper, we report a breakthrough result on the difficult task of segmentation and recognition of coloured text from the word image dataset of ICDAR robust reading competition challenge 2: reading text in scene images. We split the word image into individual colour, gray and lightness planes and enhance the contrast of each of these planes independently by a power-law transform. The discrimination factor of each plane is computed as the maximum between-class variance used in Otsu thresholding. The plane that has maximum discrimination factor is selected for segmentation. The trial version of Omnipage OCR is then used on the binarized words for recognition. Our recognition results on ICDAR 2011 and ICDAR 2003 word datasets are compared with those reported in the literature. As baseline, the images binarized by simple global and local thresholding techniques were also recognized. The word recognition rate obtained by our non-linear enhancement and selection of plance method is 72.8% and 66.2% for ICDAR 2011 and 2003 word datasets, respectively. We have created ground-truth for each image at the pixel level to benchmark these datasets using a toolkit developed by us. The recognition rate of benchmarked images is 86.7% and 83.9% for ICDAR 2011 and 2003 datasets, respectively.

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The issue of dynamic spectrum scene analysis in any cognitive radio network becomes extremely complex when low probability of intercept, spread spectrum systems are present in environment. The detection and estimation become more complex if frequency hopping spread spectrum is adaptive in nature. In this paper, we propose two phase approach for detection and estimation of frequency hoping signals. Polyphase filter bank has been proposed as the architecture of choice for detection phase to efficiently detect the presence of frequency hopping signal. Based on the modeling of frequency hopping signal it can be shown that parametric methods of line spectral analysis are well suited for estimation of frequency hopping signals if the issues of order estimation and time localization are resolved. An algorithm using line spectra parameter estimation and wavelet based transient detection has been proposed which resolves above issues in computationally efficient manner suitable for implementation in cognitive radio. The simulations show promising results proving that adaptive frequency hopping signals can be detected and demodulated in a non cooperative context, even at a very low signal to noise ratio in real time.

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The technology scene in India is at one and the same time promising, frustrating and fascinating. Three broad areas in technology development can be distinguished. The first is relatively small scale; it is typified by the absorption of products of the industrial revolution into the repertoire of the Indian artisan and craftsman, examples being diesel engines from Kolhapur and centrifugal pumps from Coimbatore. The second class is essentially 'state technology', developed at public expense by national commissions: agriculture, atomic energy and space are examples. There is a vast third area in both private and public sector, covering products for the urban consumer and the state (e.g. r defence); this area has largely remained colonial. The factors affecting the three areas of technology are described and analysed from the point of view of an Indian scientistengineer; and it is concluded that the enormous potential of the country's human and mat.erial resources is not only unrealized, but even unrecognized as yet.

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With the advent of VLSI it has become possible to map parallel algorithms for compute-bound problems directly on silicon. Systolic architecture is very good candidate for VLSI implementation because of its regular and simple design, and regular communication pattern. In this paper, a systolic algorithm and corresponding systolic architecture, a linear systolic array, for the scanline-based hidden surface removal problem in three-dimensional computer graphics have been proposed. The algorithm is based on the concept of sample spans or intervals. The worst case time taken by the algorithm is O(n), n being the number of segments in a scanline. The time taken by the algorithm for a given scene depends on the scene itself, and on an average considerable improvement over the worst case behaviour is expected. A pipeline scheme for handling the I/O process has also been proposed which is suitable for VLSI implementation of the algorithm.

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Application of ultrafast lasers to chemistry and biology has been an active area of research in the international scene for over a decade for physical and biophysical chemists. Perhaps, ultrafast laser spectroscopy is one of the most versatile tools available today to experimentally study structure and dynamics in the time domain of nanoseconds (10(-9) sec) to femtoseconds (10(-15) sec). In this article we attempt to highlight some of the recent developments in ultrafast laser spectroscopy with particular reference to vibrational spectroscopy, viz. infrared and Raman spectroscopy, in the above time domain.

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The issue of dynamic spectrum scene analysis in any cognitive radio network becomes extremely complex when low probability of intercept, spread spectrum systems are present in environment. The detection and estimation become more complex if frequency hopping spread spectrum is adaptive in nature. In this paper, we propose two phase approach for detection and estimation of frequency hoping signals. Polyphase filter bank has been proposed as the architecture of choice for detection phase to efficiently detect the presence of frequency hopping signal. Based on the modeling of frequency hopping signal it can be shown that parametric methods of line spectral analysis are well suited for estimation of frequency hopping signals if the issues of order estimation and time localization are resolved. An algorithm using line spectra parameter estimation and wavelet based transient detection has been proposed which resolves above issues in computationally efficient manner suitable for implementation in cognitive radio. The simulations show promising results proving that adaptive frequency hopping signals can be detected and demodulated in a non cooperative context, even at a very low signal to noise ratio in real time.

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The physics of the solid state has grown into that of condensed matter and is now expanding into the study of a bewildering variety of complex systems. After a brief survey of this progression, I enquire into the health of solid state physics; many signs of vitality and growth are found. The Indian scene in this field is briefly sketched, and some suggestions are offered on how to make it more lively,

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A systematic procedure is outlined for scaling analysis of momentum and heat transfer in gas tungsten arc weld pools. With suitable selections of non-dimentionalised parameters, the governing equations coupled with appropriate boundary conditions are first scaled, and the relative significance of various terms appearing in them is analysed accordingly. The analysis is then used to predict the orders of magnitude of some important quantities, such as the velocity scene lit the top surface, velocity boundary layer thickness, maximum temperature increase in the pool, and time required for initiation of melting. Some of the quantities predicted from the scaling analysis can also be used for optimised selection of appropriate grid size and time steps for full numerical simulation of the process. The scaling predictions are finally assessed by comparison with numerical results quoted in the literature, and a good qualitative agreement is observed.

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Image fusion techniques are useful to integrate the geometric detail of a high-resolution panchromatic (PAN) image and the spectral information of a low-resolution multispectral (MSS) image, particularly important for understanding land use dynamics at larger scale (1:25000 or lower), which is required by the decision makers to adopt holistic approaches for regional planning. Fused images can extract features from source images and provide more information than one scene of MSS image. High spectral resolution aids in identification of objects more distinctly while high spatial resolution allows locating the objects more clearly. The geoinformatics technologies with an ability to provide high-spatial-spectral-resolution data helps in inventorying, mapping, monitoring and sustainable management of natural resources. Fusion module in GRDSS, taking into consideration the limitations in spatial resolution of MSS data and spectral resolution of PAN data, provide high-spatial-spectral-resolution remote sensing images required for land use mapping on regional scale. GRDSS is a freeware GIS Graphic User Interface (GUI) developed in Tcl/Tk is based on command line arguments of GRASS (Geographic Resources Analysis Support System) with the functionalities for raster analysis, vector analysis, site analysis, image processing, modeling and graphics visualization. It has the capabilities to capture, store, process, analyse, prioritize and display spatial and temporal data.

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Energy systems should be consistent with environmental, economic and social sustainability in order to ensure regional sustainable development. This enhances both current and future potential to meet the human needs and aspirations. Sustainable development, a process of change, in which, the exploitation of resources, the direction of investments , the orientation of technological development and institutional change are in harmony. National energy programme should prioritize the development of renewable energy sources, which offer the potentially huge sources of primary energy. The path for sustainability in the next millennium is the low energy path through wise use of energy. Energy conservation and energy efficiency measures would certainly result in meeting the energy demand with as little as half the primary supply at current levels. This requires profound structural changes in socio-economic and institutional arrangements. Environmentally sound, technically and economically viable energy pathways will sustain human progress in the long term future giving a fair and equitable share of the underprivileged and poor of the developing countries. Renewable energy is considered by some as the only hope for the survival of planet yet by others it is viewed as a marginal resource with limited resource. All too often, however, the facts behind the role that renewable energy can, and will, play in the regional energy scene are disguised or ignored as rival camps distort the evidence to suit their own objectives. It was in the light of this confusion that the Energy Research Group at Centre for Ecological Sciences, Indian Institute of Science undertook investigation in Kolar and Uttara Kannada Districts in Karnataka State, India to identify the potential contribution of several types of renewable energy sources: Solar, Wind, Hydro, Bioenergy, etc.

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This paper describes a semi-automatic tool for annotation of multi-script text from natural scene images. To our knowledge, this is the maiden tool that deals with multi-script text or arbitrary orientation. The procedure involves manual seed selection followed by a region growing process to segment each word present in the image. The threshold for region growing can be varied by the user so as to ensure pixel-accurate character segmentation. The text present in the image is tagged word-by-word. A virtual keyboard interface has also been designed for entering the ground truth in ten Indic scripts, besides English. The keyboard interface can easily be generated for any script, thereby expanding the scope of the toolkit. Optionally, each segmented word can further be labeled into its constituent characters/symbols. Polygonal masks are used to split or merge the segmented words into valid characters/symbols. The ground truth is represented by a pixel-level segmented image and a '.txt' file that contains information about the number of words in the image, word bounding boxes, script and ground truth Unicode. The toolkit, developed using MATLAB, can be used to generate ground truth and annotation for any generic document image. Thus, it is useful for researchers in the document image processing community for evaluating the performance of document analysis and recognition techniques. The multi-script annotation toolokit (MAST) is available for free download.