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4th Conference on Design and Process Integration for Microelectronic Manufacturing

作者： Sezginer, Apo Yenikaya, Bayram Huang, Hsu-Ting Kamat, Vishnu Chen, Yung-Tin Invarium Inc 1754 Technol Dr 117 San Jose CA 95110 USA SanDisk Inc Santa Clara CA 95054 USA

ISBN: (纸本)0819461997

In optical proximity correction, edges of polygons are segmented, and segments are independently moved to meet line-width or edge placement goals. The purpose of segmenting edges is to increase the degrees of freedom in proximity correction. Segmentation is usually performed according to predetermined, geometrical rules. Heuristic, model-based segmentation algorithms have been presented in the literature. We show that there is an optimal and unique way of segmenting polygon edges.

关键词： image segmentation Photomasks image processing algorithms and systems Optical proximity correction Data modeling Detection and tracking algorithms Optimization (mathematics) Tolerancing Manufacturing Semiconducting wafers

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Spatial detection of TV channel logos as outliers from the content

Spatial detection of TV channel logos as outliers from the c...

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Conferenceon Visual Communications and image processing 2006

作者： Ekin, A Braspenning, R Philips Res Videa Proc & Visual Percept Grp Eindhoven Netherlands

ISBN: (纸本)0819461172

This paper proposes a purely image-based TV channel logo detection algorithm that can detect logos independently from their motion and transparency features. The proposed algorithm can robustly detect any type of logos, such as transparent and animated, without requiring any temporal constraints whereas known methods have to wait for the occurrence of large motion in the scene and assume stationary logos. The algorithm models logo pixels as outliers from the actual scene content that is represented by multiple 3-D histograms in the YCBCR space. We use four scene histograms corresponding to each of the four corners because the content characteristics change from one image corner to another. A further novelty of the proposed algorithm is that we define image corners and the areas where we compute the scene histograms by a cinematic technique called Golden Section Rule that is used by professionals. The robustness of the proposed algorithm is demonstrated over a dataset of representative TV content.

关键词： Detection and tracking algorithms Video image processing image segmentation Motion models 3D modeling Transparency Binary data image processing algorithms and systems Opacity

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Spotting words in handwritten Arabic documents

Spotting words in handwritten Arabic documents

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Conference on Document Recognition and Retrieval XIII

作者： Srihari, Sargur Srinivasan, Harish Babu, Pavithra Bhole, Chetan SUNY Buffalo Univ Buffalo Ctr Excellence Document Anal & Recognit CEDAR Amherst NY 14228 USA

ISBN: (纸本)0819461075

The design and performance of a system for spotting handwritten Arabic words in scanned document images is presented. Three main components of the system are a word segmenter, a shape based matcher far words and a search interface. The user types in a query in English within a search window, the system finds the equivalent Arabic word, e.g., by dictionary look-up, locates word images in an indexed (segmented) set of documents. A two-step approach is employed in performing the search: (1) prototype selection: the query is used to obtain a set of handwritten samples of that word from a known set of writers (these are the prototypes), and (2) word matching: the prototypes are used to spot each occurrence of those words in the indexed document database. A ranking is performed on, the entire set of test word images- where the ranking criterion is a similarity score between each prototype word and the candidate words based on global word shape features. A database of 20, 000 word images contained in 100 scanned handwritten Arabic documents written by 10 different writers was used to study retrieval performance. Using five Writers for Providing prototypes and the other five for testing.. using manually segmented documents,. 55% precision is obtained at 50% recall. Performance increases as more writers are used for training.

关键词： image segmentation Prototyping Databases Binary data Human-machine interfaces image retrieval Neural networks image processing image processing algorithms and systems Associative arrays

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Modeling hierarchical structure of images with stochastic grammars

Modeling hierarchical structure of images with stochastic gr...

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Conference on Computational Imaging IV

作者： Wang, Wiley Wong, Tak-Shing Pollak, Ilya Bouman, Charles A. Harper, Mary P. Purdue Univ Sch Elect & Comp Engn 1285 EE Bldg W Lafayette IN 47907 USA

We construct a hierarchical image grammar model based on stochastic grammars and apply it to document images. An efficient maximum a posteriori probability estimation algorithm for this model produces accurate segment... 详细信息

ISBN: (纸本)0819461059

关键词： image segmentation Stochastic processes Associative arrays image processing algorithms and systems Current controlled current source Data modeling image classification image compression Computer engineering Visualization

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Improved MRSI with field inhomogeneity compensation

Improved MRSI with field inhomogeneity compensation

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Medical Imaging 2006 Conference

作者： Khalidov, Ildar Van De Ville, Dimitri Jacob, Mathews Lazeyras, Francois Unser, Michael Ecole Polytech Fed Lausanne Biomed Imaging Grp Lausanne Switzerland Univ Illinois Beckman Inst Urbana IL USA HUG Dept Radiol & Med Informat Geneva Switzerland

ISBN: (纸本)0819464236

Magnetic resonance spectroscopy imaging (MRSI) is a promising and developing tool in medical imaging. Because of various difficulties imposed by the imperfections of the scanner and the reconstruction algorithms, its applicability in clinical practice is rather limited. In this paper, we suggest an extension of the constrained reconstruction technique (SLIM). Our algorithm, named B-SLIM, takes into account the the measured field inhomogeneity map, which contains both the scanner's main field inhomogeneity and the object-dependent magnetic susceptibility effects. The method is implemented and tested both with synthetic and physical two-compartment phantom data. The results demonstrate significant performance improvement over the SLIM technique. At the same time, the algorithm has the same computational complexity as SLIM.

关键词： Magnetic resonance imaging image segmentation Scanners Imaging spectroscopy Magnetism Reconstruction algorithms image processing algorithms and systems Medical imaging Spectroscopy Biomedical optics

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Address block features for image-based automated mail orientation

Address block features for image-based automated mail orient...

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Conference on Document Recognition and Retrieval XIII

作者： Khan, M. Shahab Aradhye, Hrishikesh B. Cruz, Wayne T. SRI Int Machine Vis & Robot 333 Ravenswood Ave Menlo Pk CA 94025 USA

ISBN: (纸本)0819461075

When mixed mail enters a postal facility, it must first be faced and oriented so that the address is readable by automated mail processing machinery. Existing US Postal Service (USPS) automated systems face and orient domestic mail by searching for fluorescing stamps on each mail piece. However, misplaced or partially fluorescing postage causes a significant fraction of mail to be rejected. Previously, rejected mail had to be faced and oriented by hand, thus increasing mail processing cost and time. Our earlier work successfully demonstrated the utility of machine-vision-based extraction of postal delimiters-such as cancellation marks and barcodes-for camera-based mail facing and orientation. Arguably, of all the localized information sources on the envelope image, the destination address block is the richest in content and the most structured in its form and layout. This paper focuses exclusively on the destination address block image and describes new vision-based features that can be extracted and used for mail orientation. Our results on real USPS datasets indicate robust performance. The algorithms described herein will be deployed nationwide on USPS hardware in the near future.

关键词： Feature extraction image processing Cameras Error analysis image processing algorithms and systems image segmentation Optical character recognition Electronic imaging Machine vision Robotics

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Parallel algorithm for linear feature detection from airborne LiDAR data

Parallel algorithm for linear feature detection from airborn...

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Conference on Airborne Intelligence, Surveillance, Reconnaissance (ISR) systems and Applications III

作者： Mareboyana, Manohar Chi, Paul Bowie State Univ Dept Comp Sci Bowie MD 20715 USA

ISBN: (纸本)0819462659

Linear features from airport images correspond to runways, taxiways and roads. Detecting runways helps pilots to focus on runway incursions in poor visibility conditions. In this work, we attempt to detect linear features from LiDAR swath in near real time using parallel implementation on G5-based apple cluster called Xseed. Data from LiDAR swath is converted into a uniform grid with nearest neighbor interpolation. The edges and gradient directions are computed using standard edge detection algorithms such as Canny's detector. Edge linking and detecting straight-line features are described. Preliminary results on Reno, Nevada airport data are included.

关键词： LIDAR Detection and tracking algorithms image processing image segmentation Data conversion Edge detection image processing algorithms and systems Sensors Roads Visibility

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Large-scale validation of non-rigid registration algorithms for atlas-based brain image segmentation

Large-scale validation of non-rigid registration algorithms ...

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Medical Imaging 2006 Conference

作者： Wang, Qian D'Agostino, Emiliano Seghers, Dieter Maes, Frederik Vandermeulen, Dirk Suetens, Paul Katholieke Univ Leuven Univ Hosp Gasthuisberg Fac Med & Engn Med Image Comp Radiol ESAT PSI Herestr 49 B-3000 Leuven Belgium

ISBN: (纸本)0819464236

In this paper, we evaluate different non-rigid image registration methodologies in the context of atlas-based brain image segmentation. Three non-rigid voxel-based registration regularization schemes (viscous fluid, elastic and curvature-based registration) combined with the mutual information similarity measure are compared. We conduct large-scale atlas-based segmentation experiments on a set of 20 anatomically labelled MR brain images in order to find the optimal parameter settings for each scheme. The performance of the optimal registration schemes is evaluated in their capability of accurately segmenting 49 different brain sub-structures of varying size and shape.

关键词： image segmentation Brain image registration Neuroimaging image processing algorithms and systems Performance modeling Magnetic resonance imaging Data modeling Tissues image restoration

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Unsupervised Bayesian wavelet domain segmentation using Potts-Markov random field modeling

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JOURNAL OF ELECTRONIC IMAGING 2005年第4期14卷 043011.1-043011.1页

作者： Brault, P Mohammad-Djafari, A Univ Paris 11 Inst Elect Fondamentale CNRS UMR 8622 F-91405 Orsay France

We describe a new fully unsupervised image segmentation method based on a Bayesian approach and a Potts-Markov random field ( PMRF) model that are performed in the wavelet domain. A Bayesian segmentation model, based on a PMRF in the direct domain, has already been successfully developed and tested. This model performs a fully unsupervised segmentation, on images composed of homogeneous regions, by introducing a hidden Markov model ( HMM) for the regions to be classified, and Gaussian distributions for the noise and for the pixels pertaining to each region. The computation of the posterior laws, deduced from these a priori distributions for the pixels, is done by a Markov chain Monte Carlo ( MCMC) approach and uses a Gibbs sampling algorithm. The use of a high number of iterations to reach convergence in a segmentation, where the number of segments, or "classes" labels, is important, makes the algorithm rather slow for the processing of a large quantity of data like image sequences. To overcome this problem, we take advantage of the property of the wavelet coefficients, in an orthogonal decomposition, to be modeled by a mixture of two Gaussians. Thus, by projecting an observable noisy image in the wavelet domain, we are able to segment, in this same domain, the wavelet subbands in only two classes. After a decomposition up to a scale J, the main idea is to segment the coarse, and small, approximation subband with a high number of classes, and to segment all the detail ( wavelet) subbands with only two classes. The segmented wavelet domain coefficients are then reconstructed to obtain a final segmented image in the direct domain. Our tests on synthetic and natural images show that the segmentation quality stays good, even with noisy images, and shows that the segmentation times can be significantly reduced. (c) 2005 SPIE and IS&T.

关键词： image segmentation Wavelets Beam propagation method image processing algorithms and systems image quality image processing image classification Satellite imaging Satellites Hyperspectral imaging

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image fusion and unsupervised joint segmentation using a HMM and MCMC algorithms -: art. no. 023014

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JOURNAL OF ELECTRONIC IMAGING 2005年第2期14卷 1-12页

作者： Féron, O Mohammad-Djafari, A Supelec UPS CNRS UMR8506LSS F-91192 Gif Sur Yvette France

In this paper we propose a Bayesian framework for unsupervised image fusion and joint segmentation, More specifically we consider the case where we have observed images of the same object through different imaging processes or through different spectral bands (multi- or hyperspectral images). The objective of this work is then to propose a coherent approach to combine these images and obtain a joint segmentation which can be considered as the fusion result of these observations. The proposed approach is based on a hidden Markov modeling of the images where the hidden variables represent the common classification or segmentation labels. These label variables are modeled by the Potts Markov random field. We propose two particular models for the pixels in each segment (iid. or Markovian) and develop appropriate Markov chain Monte Carlo algorithms for their implementations. Finally we present some simulation results to show the relative performances of these models and mention the potential applications of the proposed methods in medical imaging and survey and security imaging systems. (c) 2005 SPIE and IS&T.

关键词： image fusion image segmentation Data fusion Data modeling Medical imaging Magnetic resonance imaging image processing algorithms and systems Monte Carlo methods Reconstruction algorithms image classification

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