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检索条件"主题词=Image processing algorithms and systems"

共 335 条记录，以下是71-80 订阅

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OFF-LINE CURSIVE HANDWRITING RECOGNITION USING NEURAL NETWORKS 4

OFF-LINE CURSIVE HANDWRITING RECOGNITION USING NEURAL NETWOR...

引用

4th International Conference on Applications of Artificial Neural Networks

作者： YANIKOGLU, BA SANDON, PA DARTMOUTH COLL DEPT MATH & COMP SCIHANOVERNH 03755

ISBN: (纸本)0819412015

Recognition of general unconstrained cursive handwriting remains largely unsolved. We present a system for recognizing off-line cursive English text guided in part by global characteristics of the handwriting. A new method for finding the letter boundaries based on minimizing a heuristic cost function is introduced. The function is evaluated at each point along the baseline of the word to find the best possible segmentation points. The algorithm tries to find all the actual letter boundaries and as few additional ones as possible. After a normalization step that removes much of the style variation, the normalized segments are classified by a one hidden layer feedforward neural network. The word recognition algorithms find the segmentation points that are likely to be extraneous and generates all possible final segmentations of the word by either keeping or removing them. Interpreting the output of the neural network as posterior probabilities of letters, it then finds the word that maximizes the probability of having produced the image, over a set of 30,000 words and over all the possible final segmentations. We compared two hypotheses for finding the likelihood of words that are in the lexicon and found that using a Hidden Markov Model of English is significantly less successful than assuming independence among the letters of a word. In our initial test involving multiple writers, 68% of the words were in the top three choices.

关键词： image segmentation Neural networks Artificial neural networks Detection and tracking algorithms Stochastic processes image processing algorithms and systems Network architectures Statistical modeling Edge detection Mathematics

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HIERARCHICAL VECTOR REPRESENTATION OF DOCUMENT imageS

HIERARCHICAL VECTOR REPRESENTATION OF DOCUMENT IMAGES

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Conference on Video Communications and PACS for Medical Applications

作者： ABLAMEYKO, S BEREISHIK, V PARAMONOVA, N MARCELLI, A ISHIKAWA, S BELARUSIAN ACAD SCI INST ENGN CYBERNET 220012 MINSK BELARUS

ISBN: (纸本)0819412236

A hierarchical data structure for the representation of document images in vector form is suggested, which allows to store in compact form all needed information about connected components, segments and feature points. The process steps for obtaining this data structure are described. A fast one-pass algorithm for the transformation of a large-size thinned image into the vector form is suggested. The defects which can exist in the vector representation are extracted and an algorithm for their reduction is shortly described. Experimental results are also shown.

关键词： image segmentation image processing algorithms and systems Inspection Data storage Detection and tracking algorithms Object recognition Algorithm development image processing Raster graphics 3D modeling

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DESIGN OF A REAL-TIME HIGH-QUALITY SAR PROCESSOR

DESIGN OF A REAL-TIME HIGH-QUALITY SAR PROCESSOR

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Conference on algorithms for Synthetic Aperture Radar imagery

作者： PRYDE, GC BECKETT, KDR DELVES, LM OLIVER, CJ WHITE, RG NA SOFTWARE LTD LIVERPOOLENGLAND

ISBN: (纸本)0819415340

Research at the DRA, Malvern, has resulted in a series of algorithms which are capable of yielding focused, undistorted SAR imagery. Unfortunately these can only be implemented in a fraction of a percent of real-time on a standard work-station. In parallel with the algorithm development, therefore, has been research into a real-time implementation on a parallel computer (the Meiko CS1). This paper outlines the principles behind the software architecture design to achieve the desired speed. processing functions considered include: initial motion compensation (based on accelerometer data), autofocus with phase correction, final processing and an intensity segmentation stage. Real time processing rates of about 10 MBytes/s are now routinely achieved. We indicate the compromises between processor power, available local memory and communications bandwidth needed to achieve real-time operation. Detailed timings derived from the implementation will be presented together with a discussion of the manner in which this could be varied for different SAR configurations. In parallel with the work on producing real-time high quality imagery has gone a program of research into automated image-understanding techniques. This work is now reaching the stage where reliable algorithms for several basic operations, including segmentation and change detections, exist in a form capable of processing continuous imagery at real time or near real-time rates. Provision has been made for the inclusion of these algorithms as postprocessing stages in the real-time SAR processor.

关键词： Synthetic aperture radar image processing image segmentation Radar Data processing image quality image processing algorithms and systems image resolution Distortion Satellites

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Non parametric partitioning of SAR images

Non parametric partitioning of SAR images

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Conference on image and Signal processing for Remote Sensing XII

作者： Delyon, G. Galland, F. Refregier, Ph. EGIM CNRS UMR 6133 Fresnel Inst F-13397 Marseille 20 France

ISBN: (纸本)0819464600

We describe and analyse a generalization of a parametric segmentation technique adapted to Gamma distributed SAR images to a simple non parametric noise model. The partition is obtained by minimizing the stochastic complexity of a quantized version on Q levels of the SAR image and lead to a criterion without parameters to be tuned by the user. We analyse the reliability of the proposed approach on synthetic images. The quality of the obtained partition will be studied for different possible strategies. In particular, one will discuss the reliability of the proposed optimization procedure. Finally, we will precisely study the performance of the proposed approach in comparison with the statistical parametric technique adapted to Gamma noise. These studies will be led by analyzing the number of misclassified pixels, the standard Hausdorff distance and the number of estimated regions.

关键词： image segmentation Synthetic aperture radar Statistical analysis Stochastic processes image processing Particle filters Reliability Quantization image processing algorithms and systems Optimization (mathematics)

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Impact of multi-scale retinex computation on performance of segmentation algorithms

Impact of multi-scale retinex computation on performance of ...

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Conference on Visual Information processing XIII

作者： Rahman, ZU Jobson, DJ Woodell, GA Hines, GD Coll William & Mary Dept Appl Sci Williamsburg VA 23187 USA

ISBN: (纸本)0819453617

Classical segmentation algorithms subdivide an image into its constituent components based upon some metric that defines commonality between pixels. Often, these metrics incorporate some measure of "activity" in the scene, e.g. the amount of detail that is in a region. The Multiscale Retinex with Color Restoration (MSRCR) is a general purpose, non-linear image enhancement algorithm that significantly affects the brightness, contrast and sharpness within an image. In this paper, we will analyze the impact the MSRCR has on segmentation results and performance.

关键词： image segmentation image processing Signal to noise ratio image processing algorithms and systems image enhancement image classification Visualization Chromium Imaging systems image compression

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Deep learning in the small sample size setting : Cascaded feed forward neural networks for medical image segmentation

Deep learning in the small sample size setting : Cascaded fe...

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Conference on Medical Imaging - Computer-Aided Diagnosis

作者： Gaonkar, Bilwaj Hovda, David Martin, Neil Macyszyn, Luke Univ Calif Los Angeles Los Angeles CA 90095 USA

ISBN: (纸本)9781510600201

Deep Learning, refers to large set of neural network based algorithms, have emerged as promising machine learning tools in the general imaging and computer vision domains. Convolutional neural networks (CNNs), a specific class of deep learning algorithms, have been extremely effective in object recognition and localization in natural images. A characteristic feature of CNNs, is the use of a locally connected multi layer topology that is inspired by the animal visual cortex (the most powerful vision system in existence). While CNNs, perform admirably in object identification and localization tasks, typically require training on extremely large datasets. Unfortunately, in medical image analysis, large datasets are either unavailable or are extremely expensive to obtain. Further, the primary tasks in medical imaging are organ identification and segmentation from 3D scans, which are different from the standard computer vision tasks of object recognition. Thus, in order to translate the advantages of deep learning to medical image analysis, there is a need to develop deep network topologies and training methodologies, that are geared towards medical imaging related tasks and can work in a setting where dataset sizes are relatively small. In this paper, we present a technique for stacked supervised training of deep feed forward neural networks for segmenting organs from medical scans. Each 'neural network layer' in the stack is trained to identify a sub region of the original image, that contains the organ of interest. By layering several such stacks together a very deep neural network is constructed. Such a network can be used to identify extremely small regions of interest in extremely large images, inspite of a lack of clear contrast in the signal or easily identifiable shape characteristics. What is even more intriguing is that the network stack achieves accurate segmentation even when it is trained on a single image with manually labelled ground truth. We validate th

关键词： image segmentation Neural networks Medical imaging Machine learning Computer vision technology Detection and tracking algorithms image processing algorithms and systems Machine vision Computed tomography Lung

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EXTRACTION OF 2D GROUPINGS FOR 3D OBJECT RECOGNITION 3

EXTRACTION OF 2D GROUPINGS FOR 3D OBJECT RECOGNITION

引用

Conference on Visual Information processing III

作者： ARSENEAULT, JL BERGEVIN, R LAURENDEAU, D UNIV LAVAL DEPT ELECT ENGNCOMP VIS & SYST LABQUEBEC CITY G1K 7P4QUEBECCANADA

ISBN: (纸本)081941543X

An approach for the recognition of 3D objects from single 2D views is presented. Using perceptual organization, hierarchies of features based on parallelism, co-linearity, and intersection are generated. Our local grouping algorithm is particularly inspired by the formalism defined by Etamadi et al., which is concerned with the formation of self-consistent groupings of straight lines from which all higher level groupings may be derived. Our approach extends this formalism to circular arcs. Surfaces in the scene are then extracted based on perceptual laws of symmetry and closure. The recognition process uses relational graphs of surfaces constructed by establishing the proximity, adjacency, and inclusion relations that exist between the surfaces. We identify closures which can be interpreted as the borders of the visible surfaces of objects and can also be used to describe the 2D shape of the surfaces. We show that a graph can be constructed from the relations between these closures and that similarities can be extracted from two different graphs obtained by analyzing two views of the same scene. Typical results obtained for complex indoor scenes are presented.

关键词： image segmentation Detection and tracking algorithms Object recognition Algorithm development Visual information processing Lutetium image processing algorithms and systems Computer vision technology Feature extraction Machine vision

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DETECTION AND SEGMENTATION OF BLOBS USING THE WARWICK MULTIPLE-SIMD ARCHITECTURE

DETECTION AND SEGMENTATION OF BLOBS USING THE WARWICK MULTIP...

引用

CONF ON PARALLEL ARCHITECTURES FOR image processing

作者： ATHERTON, TJ NUDD, GR CLIPPINGDALE, SC FRANCIS, ND KERBYSON, DJ PACKWOOD, RA SO, YK VAUDIN, GJB WALTON, DW Univ. of Warwick (United Kingdom)

ISBN: (纸本)0819402931

The Warwick Pyramid Machine (WPM) is an M-SIMD (Multiple-Single Instruction Multiple Data) heterogeneous pyramid architecture for image understanding. Details of the implementation are given. The properties and performance of the architecture are discussed. A generic image analysis task is the detection and identification of compact, convex, blob-like objects. The detection of such blobs is illustrated in detail with a modification of the circle Hough transform. This is shown to suit the global SIMD nature of the architecture. The subsequent stage of segmentation demonstrates the local processing capabilities of the M-SIMD architecture. The image analysis examples reported use forward-looking infrared images of vehicles, and electron micrographs of virus particles. In both cases the aim is to detect candidate regions of the image for further detailed analysis.

关键词： image segmentation image processing image analysis image enhancement image processing algorithms and systems Hough transforms Photomicroscopy Computer architecture image filtering Particles

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image-CODING THROUGH PREDICTIVE VECTOR QUANTIZATION (PVQ) 15

IMAGE-CODING THROUGH PREDICTIVE VECTOR QUANTIZATION (PVQ)

引用

CONF ON APPLICATIONS OF DIGITAL image processing 15

作者： NARAYAN, A RAMABADRAN, TV Iowa State Univ. (United States)

ISBN: (纸本)0819409448

This paper describes a Predictive Vector Quantizer (PVQ) for coding grayscale images. The method described can be regarded as an extention of an existing speech coding algorithm in 1- dimension to 2-dimensional images. The method applies vector quantization (VQ) to innovations generated by the well known scalar Differential Pulse Code Modulation (DPCM) method. It tries to exploit the advantages of both the simplicity of DPCM and the high compressibility of VQ. Two types of code books, viz., random and deterministic, are used in the implementation. Performance results of the method with both types of codebooks are presented for industrial radiographic images. The results are also compared with reconstructions obtained using the Discrete Cosine Transform (DCT) method.

关键词： image compression Quantization Digital image processing Radiography Signal to noise ratio Receivers image processing algorithms and systems Distortion Modulation Reconstruction algorithms

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Semiautomatic extraction of building information based on mathematical morphology

Semiautomatic extraction of building information based on ma...

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15th International Conference on Geoinformatics

作者： Liu, Huiping Wang, Yonggang Luan, Qingzu Beijing Normal Univ Sch Geog State Key Lab Remote Sensing Sci Res Ctr Remote Sensing Beijing 100875 Peoples R China

ISBN: (纸本)9780819469137

An increasing number of applications of automatic extraction of building information have been taken in, such as in city plan, city development, military affairs, national defense, and high resolution remote sensing imagery provides these applications with new data sources. Based on differential morphological profile (DMP) algorithm in mathematical morphology, we introduce and develop a set of accurate and automatic scheme for figure information extraction, combining with MHN filter algorithm, region marking algorithm, area threshold segmentation algorithm and so on. First, the Maximum Homogeneity Neighbour Filter Method (MHN) was used to improve the quality of the image. Then, the derivative of the opening profile from the DMP algorithm of variable step size was in use for extraction of buildings' figure. At last, area marking and area threshold segmentation algorithm were introduced for post processing. DMP algorithm in classic definition requires constant step operator with different radius for differential. This means extraction of regular figure of buildings will get good results, but buildings with more complex shapes of will lapse by DMP. Aimed at the characters in the test field, we adopted a variable step size. By changing the constant step size for differential, our method can effectively detect not only buildings with regular shape, but also buildings with complex shape. In the end, accuracy evaluation was carried out for the extraction results in the test field and the precision reached 79.6%.

关键词： image segmentation image processing image processing algorithms and systems Algorithm development Digital filtering image filtering image enhancement Mathematical morphology image quality Remote sensing

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