825 resultados para Optical character recognition devices.


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In this paper, we presents the characterization technique of high-speed optoelectronics devices based electrical and optical spectra, which is as important access to the devices performance as the prevalent vector network analyzer (VNA) sweeping method. The measurement of additional modulation of laser and frequency response of photodetector from electrical spectra, and the estimation of the modulation indexes and the chirp parameters of directly modulated lasers based on optical spectra analysis, are given as examples.

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O presente trabalho tem por objectivo o estudo de novos dispositivos fotónicos aplicados a sistemas de comunicações por fibra óptica e a sistemas de processamento de sinais RF. Os dispositivos apresentados baseiam-se em processamento de sinal linear e não linear. Dispositivos lineares ópticos tais como o interferómetro de Mach-Zehnder permitem adicionar sinais ópticos com pesos fixos ou sintonizáveis. Desta forma, este dispositivo pode ser usado respectivamente como um filtro óptico em amplitude com duas saídas complementares, ou, como um filtro óptico de resposta de fase sintonizável. O primeiro princípio de operação serve como base para um novo sistema fotónico de medição em tempo real da frequência de um sinal RF. O segundo princípio de operação é explorado num novo sistema fotónico de direccionamento do campo eléctrico radiado por um agregado de antenas, e também num novo compensador sintonizável de dispersão cromática. O processamento de sinal é não linear quando sinais ópticos são atrasados e posteriormente misturados entre si, em vez de serem linearmente adicionados. Este princípio de operação está por detrás da mistura de um sinal eléctrico com um sinal óptico, que por sua vez é a base de um novo sistema fotónico de medição em tempo real da frequência de um sinal RF. A mistura de sinais ópticos em meios não lineares permite uma operação eficiente numa grande largura espectral. Tal operação é usada para realizar conversão de comprimento de onda sintonizável. Um sinal óptico com multiplexagem no domínio temporal de elevada largura de banda é misturado com duas bombas ópticas não moduladas com base em processos não lineares paramétricos num guia de ondas de niobato de lítio com inversão periódica da polarização dos domínios ferroeléctricos. Noutro trabalho, uma bomba pulsada em que cada pulso tem um comprimento de onda sintonizável serve como base a um novo conversor de sinal óptico com multiplexagem no domínio temporal para um sinal óptico com multiplexagem no comprimento de onda. A bomba é misturada com o sinal óptico de entrada através de um processo não linear paramétrico numa fibra óptica com parâmetro não linear elevado. Todos os dispositivos fotónicos de processamento de sinal linear ou não linear propostos são experimentalmente validados. São também modelados teoricamente ou através de simulação, com a excepção dos que envolvem mistura de sinais ópticos. Uma análise qualitativa é suficiente nestes últimos dispositivos.

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The objective of the study is to develop a hand written character recognition system that could recognisze all the characters in the mordern script of malayalam language at a high recognition rate

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Garment information tracking is required for clean room garment management. In this paper, we present a camera-based robust system with implementation of Optical Character Reconition (OCR) techniques to fulfill garment label recognition. In the system, a camera is used for image capturing; an adaptive thresholding algorithm is employed to generate binary images; Connected Component Labelling (CCL) is then adopted for object detection in the binary image as a part of finding the ROI (Region of Interest); Artificial Neural Networks (ANNs) with the BP (Back Propagation) learning algorithm are used for digit recognition; and finally the system is verified by a system database. The system has been tested. The results show that it is capable of coping with variance of lighting, digit twisting, background complexity, and font orientations. The system performance with association to the digit recognition rate has met the design requirement. It has achieved real-time and error-free garment information tracking during the testing.

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Features derived from the trispectra of DFT magnitude slices are used for multi-font digit recognition. These features are insensitive to translation, rotation, or scaling of the input. They are also robust to noise. Classification accuracy tests were conducted on a common data base of 256× 256 pixel bilevel images of digits in 9 fonts. Randomly rotated and translated noisy versions were used for training and testing. The results indicate that the trispectral features are better than moment invariants and affine moment invariants. They achieve a classification accuracy of 95% compared to about 81% for Hu's (1962) moment invariants and 39% for the Flusser and Suk (1994) affine moment invariants on the same data in the presence of 1% impulse noise using a 1-NN classifier. For comparison, a multilayer perceptron with no normalization for rotations and translations yields 34% accuracy on 16× 16 pixel low-pass filtered and decimated versions of the same data.

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An application of image processing techniques to recognition of hand-drawn circuit diagrams is presented. The scanned image of a diagram is pre-processed to remove noise and converted to bilevel. Morphological operations are applied to obtain a clean, connected representation using thinned lines. The diagram comprises of nodes, connections and components. Nodes and components are segmented using appropriate thresholds on a spatially varying object pixel density. Connection paths are traced using a pixel-stack. Nodes are classified using syntactic analysis. Components are classified using a combination of invariant moments, scalar pixel-distribution features, and vector relationships between straight lines in polygonal representations. A node recognition accuracy of 82% and a component recognition accuracy of 86% was achieved on a database comprising 107 nodes and 449 components. This recogniser can be used for layout “beautification” or to generate input code for circuit analysis and simulation packages

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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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Submicrometer channel and rib waveguides based on SOI (Silicon-On-Insulator) have been designed and fabricated with electron-beam lithography and inductively coupled plasma dry etching. Propagation loss of 8.39dB/mm was measured using the cut-back method. Based on these so-called nanowire waveguides, we have also demonstrated some functional components with small dimensions, including sharp 90 degrees bends with radius of a few micrometers, T-branches, directional couplers and multimode interferometer couplers.

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Electro-optical modulator with dual capacitors is designed and based on this design basic configuration of device is realized in laboratory. Exceeding GHz switching speed and high phase modulation efficiency can be expected with this device.

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Nearest neighbor retrieval is the task of identifying, given a database of objects and a query object, the objects in the database that are the most similar to the query. Retrieving nearest neighbors is a necessary component of many practical applications, in fields as diverse as computer vision, pattern recognition, multimedia databases, bioinformatics, and computer networks. At the same time, finding nearest neighbors accurately and efficiently can be challenging, especially when the database contains a large number of objects, and when the underlying distance measure is computationally expensive. This thesis proposes new methods for improving the efficiency and accuracy of nearest neighbor retrieval and classification in spaces with computationally expensive distance measures. The proposed methods are domain-independent, and can be applied in arbitrary spaces, including non-Euclidean and non-metric spaces. In this thesis particular emphasis is given to computer vision applications related to object and shape recognition, where expensive non-Euclidean distance measures are often needed to achieve high accuracy. The first contribution of this thesis is the BoostMap algorithm for embedding arbitrary spaces into a vector space with a computationally efficient distance measure. Using this approach, an approximate set of nearest neighbors can be retrieved efficiently - often orders of magnitude faster than retrieval using the exact distance measure in the original space. The BoostMap algorithm has two key distinguishing features with respect to existing embedding methods. First, embedding construction explicitly maximizes the amount of nearest neighbor information preserved by the embedding. Second, embedding construction is treated as a machine learning problem, in contrast to existing methods that are based on geometric considerations. The second contribution is a method for constructing query-sensitive distance measures for the purposes of nearest neighbor retrieval and classification. In high-dimensional spaces, query-sensitive distance measures allow for automatic selection of the dimensions that are the most informative for each specific query object. It is shown theoretically and experimentally that query-sensitivity increases the modeling power of embeddings, allowing embeddings to capture a larger amount of the nearest neighbor structure of the original space. The third contribution is a method for speeding up nearest neighbor classification by combining multiple embedding-based nearest neighbor classifiers in a cascade. In a cascade, computationally efficient classifiers are used to quickly classify easy cases, and classifiers that are more computationally expensive and also more accurate are only applied to objects that are harder to classify. An interesting property of the proposed cascade method is that, under certain conditions, classification time actually decreases as the size of the database increases, a behavior that is in stark contrast to the behavior of typical nearest neighbor classification systems. The proposed methods are evaluated experimentally in several different applications: hand shape recognition, off-line character recognition, online character recognition, and efficient retrieval of time series. In all datasets, the proposed methods lead to significant improvements in accuracy and efficiency compared to existing state-of-the-art methods. In some datasets, the general-purpose methods introduced in this thesis even outperform domain-specific methods that have been custom-designed for such datasets.

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We describe a 42.6 Gbit/s all-optical pattern recognition system which uses semiconductor optical amplifiers (SOAs). A circuit with three SOA-based logic gates is used to identify the presence of specific port numbers in an optical packet header.

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The enhanced optical properties of metal films periodically perforated with an array of sub-wavelength size holes have recently been widely studied in the field of surface plasmon optics. The ability to design the optical transmission of such nanostructures, which act as plasmonic crystals, by varying their geometrical parameters gives them great flexibility for numerous applications in photonics, opto-electronics, and sensing. Transforming these passive optical elements into devices that may be actively controlled has presented a new challenge. Here, we report on the realization of an electrically controlled nanostructured optical system based on the unique properties of surface plasmon polaritonic crystals in contact with a liquid crystal (LC) layer. We discuss the effect of LC layer modulation on the surface plasmon dispersion, the related optical transmission and the underlying mechanism. The reported effect may be used to achieve active spectral tuneability and switching in a wide range of applications.

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The Schiff base, 3-hydroxyquinoxaline-2-carboxalidine-4-aminoantipyrine, was synthesized by the condensation of 3-hydroxyquinoxaline-2-carboxaldehyde with 4-aminoantipyrine. HPLC, FT-IR and NMR spectral data revealed that the compound exists predominantly in the amide tautomeric form and exhibits both absorption and fluorescence solvatochromism, large stokes shift, two electron quasireversible redox behaviour and good thermal stability, with a glass transition temperature of 104oC. The third-order non-linear optical character was studied using open aperture Z-scan methodology employing 7 ns pulses at 532 nm. The third-order non-linear absorption coefficient, b, was 1.48 x 10-6 cm W-1 and the imaginary part of the third-order non-linear optical susceptibility, Im c(3), was 3.36 x10-10 esu. The optical limiting threshold for the compound was found to be 340 MW cm-2.