888 resultados para Database application, Biologia cellulare, Image retrieval


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The efficacy of the multifractal spectrum as a tool for characterizing images has been studied. This spectrum has been computed for digitized images of the nucleus of human cervical cancer cells and it was observed that the entire spectrum is almost fully reproduced for a normal cell while only the right half (q<0) of the spectrum is reproduced for a cancerous cell. Cells in stages in between the two extremes show a shortening of the left half of the spectrum proportional to their condition. The extent of this shortening has been found to be sufficient to permit a classification between three classes of cells at varying distances from a basal cancerous layer-the superficial cells, the intermediate cells and the parabasal cells. This technique may be used for automatic screening of the population while also indicating the stage of malignancy

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A novel approach for lossless as well as lossy compression of monochrome images using Boolean minimization is proposed. The image is split into bit planes. Each bit plane is divided into windows or blocks of variable size. Each block is transformed into a Boolean switching function in cubical form, treating the pixel values as output of the function. Compression is performed by minimizing these switching functions using ESPRESSO, a cube based two level function minimizer. The minimized cubes are encoded using a code set which satisfies the prefix property. Our technique of lossless compression involves linear prediction as a preprocessing step and has compression ratio comparable to that of JPEG lossless compression technique. Our lossy compression technique involves reducing the number of bit planes as a preprocessing step which incurs minimal loss in the information of the image. The bit planes that remain after preprocessing are compressed using our lossless compression technique based on Boolean minimization. Qualitatively one cannot visually distinguish between the original image and the lossy image and the value of mean square error is kept low. For mean square error value close to that of JPEG lossy compression technique, our method gives better compression ratio. The compression scheme is relatively slower while the decompression time is comparable to that of JPEG.

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This work describes an online handwritten character recognition system working in combination with an offline recognition system. The online input data is also converted into an offline image, and parallely recognized by both online and offline strategies. Features are proposed for offline recognition and a disambiguation step is employed in the offline system for the samples for which the confidence level of the classifier is low. The outputs are then combined probabilistically resulting in a classifier out-performing both individual systems. Experiments are performed for Kannada, a South Indian Language, over a database of 295 classes. The accuracy of the online recognizer improves by 11% when the combination with offline system is used.

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Novel pyrroloisoquinolines 4 are obtained from 1-methyl-3,4-dihydroisoquinolines 1 by the action of POCl3 and DMF, along with the expected mono- and dialdehydes 2 and 3 respectively and also directly from N-acetyl-2-phenethylamines.

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Irradiation of 4-aryl-4-alkylhex-5-en-2-ones (e.g. 1a) or 5-aryl-4-alkylhex-5-en-2-ones (e.g. 2a) adsorbed on montmorillonite K-10 in a commercial microwave oven furnishes the multialkylated naphthalenes (e.g. 3).

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In this work, a procedure is presented for the reconstruction of biological organs from image sequences obtained through CT-scan. Although commercial software, which can accomplish this task, are readily available, the procedure presented here needs only free software. The procedure has been applied to reconstruct a liver from the scan data available in literature. 3D biological organs obtained this way can be used for the finite element analysis of biological organs and this has been demonstrated by carrying out an FE analysis on the reconstructed liver.

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CDS/ISIS, an advanced non-numerical information storage and retrieval software was developed by UNESCO. With the emergence of WWW technology, most of the information activities are becoming Web-centric. Libraries and information providers are taking advantage of these Internet developments to provide access to their resources/information on the Web. A number of tools are now available for publishing CDS/ISIS databases on the Internet. One such tool is the WWWISIS Web gateway software, developed by BIREME, Brazil. This paper illustrates porting of sample records from a bibliographic database into CDS/ISIS, and then publishing this database on the Internet using WWWISIS.

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Rv2118c belongs to the class of conserved hypothetical proteins from Mycobacterium tuberculosis H37Rv. The crystal structure of Rv2118c in complex with S-adenosyl-Image -methionine (AdoMet) has been determined at 1.98 Å resolution. The crystallographic asymmetric unit consists of a monomer, but symmetry-related subunits interact extensively, leading to a tetrameric structure. The structure of the monomer can be divided functionally into two domains: the larger catalytic C-terminal domain that binds the cofactor AdoMet and is involved in the transfer of methyl group from AdoMet to the substrate and a smaller N-terminal domain. The structure of the catalytic domain is very similar to that of other AdoMet-dependent methyltransferases. The N-terminal domain is primarily a β-structure with a fold not found in other methyltransferases of known structure. Database searches reveal a conserved family of Rv2118c-like proteins from various organisms. Multiple sequence alignments show several regions of high sequence similarity (motifs) in this family of proteins. Structure analysis and homology to yeast Gcd14p suggest that Rv2118c could be an RNA methyltransferase, but further studies are required to establish its functional role conclusively.

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Digital Image Correlation and Tracking (DIC/DDIT) is an optical method that employs tracking & image registration techniques for accurate 2D and 3D measurements of changes in images. This is often used to measure deformation (engineering), displacement, and strain, but it is widely applied in many areas of science and engineering. One very common application is for measuring the motion of an optical mouse.

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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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Fully structured and matured open source spatial and temporal analysis technology seems to be the official carrier of the future for planning of the natural resources especially in the developing nations. This technology has gained enormous momentum because of technical superiority, affordability and ability to join expertise from all sections of the society. Sustainable development of a region depends on the integrated planning approaches adopted in decision making which requires timely and accurate spatial data. With the increased developmental programmes, the need for appropriate decision support system has increased in order to analyse and visualise the decisions associated with spatial and temporal aspects of natural resources. In this regard Geographic Information System (GIS) along with remote sensing data support the applications that involve spatial and temporal analysis on digital thematic maps and the remotely sensed images. Open source GIS would help in wide scale applications involving decisions at various hierarchical levels (for example from village panchayat to planning commission) on economic viability, social acceptance apart from technical feasibility. GRASS (Geographic Resources Analysis Support System, http://wgbis.ces.iisc.ernet.in/grass) is an open source GIS that works on Linux platform (freeware), but most of the applications are in command line argument, necessitating a user friendly and cost effective graphical user interface (GUI). Keeping these aspects in mind, Geographic Resources Decision Support System (GRDSS) has been developed with functionality such as raster, topological vector, image processing, statistical analysis, geographical analysis, graphics production, etc. This operates through a GUI developed in Tcltk (Tool command language / Tool kit) under Linux as well as with a shell in X-Windows. GRDSS include options such as Import /Export of different data formats, Display, Digital Image processing, Map editing, Raster Analysis, Vector Analysis, Point Analysis, Spatial Query, which are required for regional planning such as watershed Analysis, Landscape Analysis etc. This is customised to Indian context with an option to extract individual band from the IRS (Indian Remote Sensing Satellites) data, which is in BIL (Band Interleaved by Lines) format. The integration of PostgreSQL (a freeware) in GRDSS aids as an efficient database management system.

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This paper presents a low cost but high resolution retinal image acquisition system of the human eye. The images acquired by a CMOS image sensor are communicated through the Universal Serial Bus (USB) interface to a personal computer for viewing and further processing. The image acquisition time was estimated to be 2.5 seconds. This system can also be used in telemedicine applications.

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We propose the design and implementation of hardware architecture for spatial prediction based image compression scheme, which consists of prediction phase and quantization phase. In prediction phase, the hierarchical tree structure obtained from the test image is used to predict every central pixel of an image by its four neighboring pixels. The prediction scheme generates an error image, to which the wavelet/sub-band coding algorithm can be applied to obtain efficient compression. The software model is tested for its performance in terms of entropy, standard deviation. The memory and silicon area constraints play a vital role in the realization of the hardware for hand-held devices. The hardware architecture is constructed for the proposed scheme, which involves the aspects of parallelism in instructions and data. The processor consists of pipelined functional units to obtain the maximum throughput and higher speed of operation. The hardware model is analyzed for performance in terms throughput, speed and power. The results of hardware model indicate that the proposed architecture is suitable for power constrained implementations with higher data rate

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With the introduction of 2D flat-panel X-ray detectors, 3D image reconstruction using helical cone-beam tomography is fast replacing the conventional 2D reconstruction techniques. In 3D image reconstruction, the source orbit or scanning geometry should satisfy the data sufficiency or completeness condition for exact reconstruction. The helical scan geometry satisfies this condition and hence can give exact reconstruction. The theoretically exact helical cone-beam reconstruction algorithm proposed by Katsevich is a breakthrough and has attracted interest in the 3D reconstruction using helical cone-beam Computed Tomography.In many practical situations, the available projection data is incomplete. One such case is where the detector plane does not completely cover the full extent of the object being imaged in lateral direction resulting in truncated projections. This result in artifacts that mask small features near to the periphery of the ROI when reconstructed using the convolution back projection (CBP) method assuming that the projection data is complete. A number of techniques exist which deal with completion of missing data followed by the CBP reconstruction. In 2D, linear prediction (LP)extrapolation has been shown to be efficient for data completion, involving minimal assumptions on the nature of the data, producing smooth extensions of the missing projection data.In this paper, we propose to extend the LP approach for extrapolating helical cone beam truncated data. The projection on the multi row flat panel detectors has missing columns towards either ends in the lateral direction in truncated data situation. The available data from each detector row is modeled using a linear predictor. The available data is extrapolated and this completed projection data is backprojected using the Katsevich algorithm. Simulation results show the efficacy of the proposed method.