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检索条件"机构=Lab for Image Processing and Computer Graphics - LAPIX"

共 41 条记录，以下是21-30 订阅

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Using Acceleration Data from Smartphones to Interact with 3D Medical Data

Using Acceleration Data from Smartphones to Interact with 3D...

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Brazilian Symposium on computer graphics and image processing (SIBGRAPI)

作者： Mateus de Souza Diego Dias Bispo Carvalho Peter Barth Jeferson Vieira Ramos Eros Comunello Aldo von Wangenheim LAPIX - Laboratory for Image Processing and Computer Graphics Federal University of Santa Catarina Florianópolis Brazil Hochschule RheinMain Wiesbaden Germany

Accelerometers integrated in modern smartphones pave the way to intuitively use gestures for collaboratively controlling interactive applications. Using and holding smartphones has become natural and ensures user acceptance as well as intuitive handling. We focus on using accelerators in several smartphones at the same time to interactively control a medical imaging solution. To this end, we introduce a framework to collect, modify, and distribute acceleration sensor data from multiple smartphones and integrate it with a medical imaging system which results in an environment suitable for e.g. doctors reviewing and explaining diagnostic findings. We performed some experiments to evaluate the usability of this approach and present an ongoing research in adapting the smartphone interface to physical simulation applications.

关键词： Smart phones Acceleration Biomedical imaging Medical services Three dimensional displays Skull Mice

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A fast lossless compression algorithm for Arabic textual images

A fast lossless compression algorithm for Arabic textual ima...

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2011 2nd IEEE International Conference on Signal and image processing Applications, ICSIPA 2011

作者： Alzahir, Saif Graphics Image Processing and Multimedia Lab Computer Science University of Northern British Columbia Prince George BC V2N 4Z9 Canada

ISBN: (纸本)9781457702419

In recent years, an unparalleled volume of textual information was transported over the Internet via email, chatting, blogging, twittering, digital libraries, and information retrieval systems. As the volume of text data has exceeded 40% of the total volume of traffic on the Internet, compressing textual data becomes imperative. Many algorithms were introduced and employed for this purpose including Huffman encoding, arithmetic encoding, the Ziv-Lempel family, Dynamic Markov Compression, and Burrow-Wheeler Transform. In this paper, a novel algorithm for compressing textual images is presented. The algorithm comprises of two parts: (i) a fixed-to-variable codebook;and (ii) row and column reduction coding scheme, RCRC. Simulation results on a large number of Arabic textual images show that this algorithm has a compression ratio of approximately 87%, which exceeds published results including those of JBIG2. © 2011 IEEE.

关键词： Signal encoding

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UTILIZING FIXED-SIZE SYSTOLIC ARRAYS FOR LARGE COMPUTATIONAL PROBLEMS

UTILIZING FIXED-SIZE SYSTOLIC ARRAYS FOR LARGE COMPUTATIONAL...

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SATELLITE CONF AT THE 1988 BIANNUAL INTERNATIONAL CONF ON PATTERN RECOGNITION : RECENT ISSUES IN PATTERN ANALYSIS AND RECOGNITION

作者： PETKOV, N Int. Lab. Image Processing and Computer Graphics Central Inst. Cybernetics and Info. Processes Kurstr. 33 P.O. Box 1298 Berlin GDR-1086 Germany

A new scheme for partitioning systolic algorithms is presented. It is based on the time-sharing properties of the c-slow circuits. The technique is amenable to formalization and holds high potential for automatization... 详细信息

ISBN: (纸本)0387518150

关键词： C-slow circuits Convolution Partitioning Systolic algorithms

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Running order statistics on a bit-level systolic array 4th

Running order statistics on a bit-level systolic array

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4th International Workshop on Parallel processing by Cellular Automata and Arrays, Parcella 1988

作者： Petkov, N. Int’l Lab. Image Processing and Computer Graphics Central Institute of Cybernetics and Information Processes Kurstr. 33 P.O. Box 1298 BerlinDDR-1086 Germany

ISBN: (纸本)9783540506478

A two-dimensional bit-level systolic array for running order statistics is presented. Both word-level and bit-level parallelism are employed. The array is extremely easy to implement in VLSI, because its cells are very small and simple. Since extensive pipe-lining is used at both word and bit level, the array can be operated at very high clock frequencies achieving very high throughputs. The algorithm delivers full running order statistics in time θ(n) and area θ[n(w+logn)] where n is the cardinality of the processed set and w is the word width of its elements. © by Akademie-Verlag Berlin 1989.

关键词： Systolic arrays

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Multi-Contextual and Multi-Aspect Analysis for Road Surface Type Classification Through Inertial Sensors and Deep Learning

Multi-Contextual and Multi-Aspect Analysis for Road Surface ...

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Brazilian Symposium on Computing System Engineering (SBESC)

作者： Jeferson Menegazzo Aldo von Wangenheim Graduate Program in Computer Science (PPGCC) Image Processing and Computer Graphics Lab (LAPIX) Brazilian National Institute for Digital Convergence (INCoD) Federal University of Santa Catarina (UFSC) Florianópolis Brazil

ISBN: (数字)9781728182865

ISBN: (纸本)9781728182872

The demand for a variety of situational data from the traffic environment and its participants has intensified with the development of applications in Intelligent Transport Systems (ITS). Among these data, the road surface type classification is one of the most important and can be used in the entire ITS domain. For its widespread application, it is necessary to employ a robust technology for the generation of raw data and to develop of a reliable and stable model to process these data in order to produce the classification. The developed model must operate correctly in different vehicles, under different driving styles and in different environments in which a vehicle can travel. In this work we employ inertial sensors, represented by accelerometers and gyroscopes, which are a safe, non-polluting, and low-cost alternative, ideal for large-scale use. We collect nine datasets with contextual variations, including three different vehicles, with three different drivers, in three different environments, in which there are three different road surface types, in addition to variations in the conservation state and presence of anomalies and obstacles such as potholes and speed bumps. After data collection, these data were used in experiments to evaluate various aspects, such as the influence of the vehicle data collection point, the analysis domain, the model input features, and the data window. Afterwards we evaluated the learning and generalization capacity of the models for unknown contexts. In a third step, the data were used in three Deep Neural Network (DNN) models: LSTM-based, GRU-based, and CNN-based. Through a multi-aspect and multi-contextual analysis, we considered the CNN-based model as the best one, which obtained an average accuracy between the data collection placements of 94.27% for learning and 92.70% for validation, classifying the road surface between asphalt, cobblestone or dirt road segments.

关键词： Roads Sensors Data models Vehicles Sensor systems Deep learning Data collection

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A near minimum sparse pattern coding based scheme for binary image compression

A near minimum sparse pattern coding based scheme for binary...

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IEEE International Conference on image processing

作者： S. Zahir M. Naqvi Image Processing Graphics and Multimedia Lab Department of Computer Science UNBC Prince George Canada

In this paper, we propose a near minimum sparse pattern coding based scheme for binary image compression. Sparse patterns such as those obtained from prediction, image differencing, and other methods can be coded efficiently using the scheme proposed in this paper. In this research we apply our scheme on coordinate representation of rectangular regions via a number of matrices. Such representations allow for efficiently coding these vertices, and hence compress the image significantly. Simulation results show that the proposed scheme outperformed previously published methods for coordinate data coding by nearly 17%. This scheme has low complexity compared with JBIG2.

关键词： image coding Block codes image processing computer graphics computer science Sparse matrices Decorrelation Probability Partitioning algorithms Standards publication

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A New Efficient Algorithm for Lossless Binary image Compression

A New Efficient Algorithm for Lossless Binary Image Compress...

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Canadian Conference on Electrical and computer Engineering (CCECE)

作者： Lele Zhou Saif Zahir Image Processing Graphics and Multimedia Lab Computer Science Department University of Northern British Columbia Canada

Binary image compression is desirable for a wide range of applications, such as digital libraries, map archives, fingerprint databases, facsimile, etc. In this paper, we present a new highly efficient algorithm for lossless binary image compression. The proposed algorithm introduces a new method, direct redundancy elimination, to efficiently exploit the two-dimensional redundancy of an image, as well as a novel dynamic context model to improve the efficiency of arithmetic coding. Simulation results show that the proposed algorithm has comparable compression ratio to JBIG standard. In many cases, the proposed algorithm outperforms the JBIG standard

关键词： image coding Arithmetic Context modeling image processing computer graphics computer science Electronic mail Multimedia databases Application software Software libraries

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A Fast Lossless Compression Scheme for Digital Map images Using Color Separation

A Fast Lossless Compression Scheme for Digital Map Images Us...

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IEEE International Conference on Acoustics, Speech, and Signal processing

作者： Saif Zahir Arber Borici Graphics and Image Processing Lab Computer Science University of N. British Columbia BC Canada

ISBN: (纸本)9781424442959

In this paper, we present a fast lossless compression scheme for digital map images in the raster image format. This work contains two main contributions. The first is centered around the creation of a code book that is based on symbol-entropy. The second contribution is the introduction of a new row-column reduction algorithm. Our scheme proceeds as follows: we determine the number of different colors in a given map image. For each color, we create a separate bi-level data layer, one for the color and the second is for the background. Then, we compress each bi-level layer individually using the proposed method, which is based on symbol-entropy in conjunction with our row-column reduction coding algorithm. Our experimental results show that our lossless compression scheme achieved on average a compression equal to 0.035 bits per pixel which is better than most reported results in the literature or comparable to some. Moreover, our scheme is simple and fast.

关键词： Lossless image compression entropy symbol entropy map images map image compression GIS map compression

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Visibly accurate model-based binary image compression scheme

Visibly accurate model-based binary image compression scheme

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IEEE International Conference on Signal and image processing Applications (ICSIPA)

作者： Saif alZahir Image Processing Graphics and Multimedia Lab Computer Science Department UNBC Prince George BC Canada

In this paper we propose a model-based binary image compression scheme. In this scheme, we merge one-dimensional (1-D) blocks of black pixels of the input binary image with those in consecutive rows into larger blocks using mathematical models that preserve the quality of the image. This process reduces the number of vertices when the image is segmented into rectangles for compression. The top-left and the bottom-right vertices of each generated rectangle are then identified and the coordinates of which are efficiently encoded. The model for merging the blocks was obtained through extracting the data values involving the blocks of various widths and the subjective tolerance of an average viewer. The data values are then plotted on a Cartesian plane and approximated with linear, logarithmic, and polynomial functions. Simulation results show that the images after merging using the proposed model have less number of rectangles without any obvious image distortion and have higher compression ratio those rectangular partitioning methods in the literature.

关键词： image coding Mathematical model Merging Polynomials image segmentation Simulation Correlation

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A Web-Based Tool for Semi-Automated Segmentation of Histopathological images Using Nonlinear Color Classifiers

A Web-Based Tool for Semi-Automated Segmentation of Histopat...

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Annual IEEE Symposium on computer-Based Medical Systems

作者： Marcelo Dornbusch Lopes Antonio C. Sobieranski Aldo Von Wangenheim Eros Comunello INCoD - National Brazilian Institute for Digital Convergence / LAPIX - Image Processing and Computer Graphics Lab - Federal University of Santa Catarina Brazil Postgraduate Program in Applied Computing University of Itajai Valley - UNIVALI INCoD (Nat. Brazilian Inst. for Digital Convergence) LAPIX (Image Process. & Comput. Graphics Lab.) Universidade Federal de Santa Catarina Florianopolis SC BR

ISBN: (纸本)9781467390378

Histopathological staining is a technique widely used to highlight biological states or pharmacological activities in uman tissue. A quantitative analysis of the resulting images can produce biomarkers for diseases or even other specific conditions, thus providing valuable information for diagnosis and prognosis. Since biomarkers require measurements to be made in an objective and consistent way, software systems are employed to provide this quantitative analysis. For measurements to be reproducible, the same methods must be available across different laboratories. In this paper, we present a tool that allows users to perform quantitative analyses over the web, thus providing an efficient environment not only for individual cases to be evaluated, but also for users to share a common ground when making measurements. The classification method used by the tool to segment stained pixels is performed by a similarity function based on the polynomial version of the Mahalanobis distance, which is nonlinear and provides very robust classification for m-dimensional feature spaces. Furthermore, the similarity function can be generalized in the tool, so that images can be classified by reusing parameters of previous cases. The results of our web-based approach were compared with established ground-truth data sets, producing sensitivity, specificity and fitness values of 97.09%, 98.70%, and 97.90%.

关键词： image color analysis image segmentation Biomarkers Sensitivity Inspection Servers Statistical analysis

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