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检索条件"主题词=Detection and tracking algorithms"

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NEURAL NETWORKS IN SEGMENTATION OF MAMMOGRAPHIC MICROCALCIFICATIONS

NEURAL NETWORKS IN SEGMENTATION OF MAMMOGRAPHIC MICROCALCIFI...

引用

Conference on Image Processing

作者： AGHDASI, F WARD, RK PALCIC, B UNIV BRITISH COLUMBIA DEPT ELECT ENGNVANCOUVER V6T 1W5BCCANADA

ISBN: (纸本)081941462X

Automatic detection and segmentation of microcalcifications may be achieved by application of algorithmic techniques or by use of artificial neural networks. We selected two neural network architectures and implemented object detection techniques on them. Further we have developed two algorithmic approaches to segment microcalcifications. In the first algorithm, thresholding of local image gray level histogram is used for object segmentation. In the first pass each object is labeled and object boundaries are marked but they are not segmented from the background. In the second pass the discontinuities due to region boundaries are corrected for, by allocating a unique threshold value for each object commensurate with the local background. In an alternative algorithm we employ edge detection to identify the pixels that may potentially belong to microcalcifications. Region growing techniques are then applied and the resulting segmented objects are subjected to tests involving shape, size and gradient.

关键词： Image segmentation Neural networks Mammography Neurons Image processing algorithms and systems Image processing Breast Cancer detection and tracking algorithms Edge detection

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ARABIC CHARACTER-RECOGNITION

ARABIC CHARACTER-RECOGNITION

引用

Conference on Document Recognition

作者： ALLAM, M CAIRO UNIV GIZAEGYPT

ISBN: (纸本)081941476X

This paper presents a complete system for learning and recognizing Arabic characters. Arabic OCR faces technical problems not encountered in other languages such as cursiveness, overriding and overlapping of characters, multiple shapes per character and the presence of vowels above and below the characters. The proposed approach relies on the fact that the process of connecting Arabic characters to produce cursive writing tends to form a fictitious baseline. During preprocessing, contour analysis provides both component isolation and baseline location. In the feature extraction phase, the words are processed from right to left to generate a sequence of labels. Each label is one of a predetermined codebook that represents all possible bit distribution with respect to the baseline. At a certain position, which depends on the label context, a segmentation decision is taken. During training, a model is generated for each character. This model describes the probability of the occurrence of the labels at each vertical position. During recognition, the probability of the label observation sequence is computed and accumulated. The system has been tested on different typewritten, typeset fonts and diacriticized versions of both and the evaluation results are presented.

关键词： Optical character recognition Silicon Feature extraction Computing systems Prototyping detection and tracking algorithms Information operations Lithium Lutetium Radon

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COMPARATIVE-STUDY OF FEATURE MAPPING AND SELECTION FOR ATR - EXPERIMENTS ON SAR DATA

COMPARATIVE-STUDY OF FEATURE MAPPING AND SELECTION FOR ATR -...

引用

Conference on algorithms for Synthetic Aperture Radar Imagery

作者： YU, X HOFF, LE REED, IS BUCK, D CHEN, AM SCI APPLICAT INT CORP LA JOLLACA 92037

ISBN: (纸本)0819415340

Most practical automatic target detection/recognition algorithms (ATR) need to incorporate feature mapping and extraction. The performance of the detection algorithms is strongly affected by the effectiveness of feature mapping. For this paper, the effectiveness is evaluated not only by the number of features needed to represent a signal for a given mean-square magnitude error of approximation, but also by the separability of those features from the clutter background. To investigate the effectiveness of a class of linear feature mapping and selection techniques, a comparative study is conducted in this paper using the data collected by MIT Lincoln Laboratory on the SRI Ultra Wideband (UWB) SAR sensor. This data collection was sponsored by ARPA. The feature mappings considered in this paper include conventional image transforms and modern multiresolution decompositions. The traditional image transforms, such as the discrete Fourier transform and the discrete cosine transform provide frequency domain information in the data, while the modern multiresolution decomposition, such as the discrete wavelet transform, are well-known for their capability to provide both spatial and frequency information. In the transform domain, the significant features, i.e., the features with the greatest energy, are extracted by a zonal-filtering with selected masks. The separability of the extracted target significant features from the natural clutter features are compared in terms of the estimated effective GSNR offered by the different feature mappings using the imaged vehicles and the clutter data obtained from the SRI radar. Finally the experimental receiver operating characteristic curves are also presented for the selected feature mappings.

关键词： Sensors Transform theory Associative arrays Target detection Synthetic aperture radar Discrete wavelet transforms Feature extraction Palladium Automatic target recognition detection and tracking algorithms

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SCENE OBJECT CLASSIFICATION USING MULTISPECTRAL DATA FUSION algorithms

SCENE OBJECT CLASSIFICATION USING MULTISPECTRAL DATA FUSION ...

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Conference on Space Instrumentation and Dual-Use Technologies

作者： KUZMA, TJ LAZOFSON, LE CHOE, HC CHOVAN, JD BATTELLE MEM INST COLUMBUSOH 43201

ISBN: (纸本)0819415189

Near-simultaneous, multispectral, coregistered imagery of ground target and background signatures were collected over a full diurnal cycle in visible, infrared, and ultraviolet spectrally filtered wavebands using Battelle's portable sensor suite. The imagery data were processed using classical statistical algorithms, artificial neural networks and data clustering techniques to classify objects in the imaged scenes. Imagery collected at different times throughout the day were employed to verify algorithm robustness with respect to temporal variations of spectral signatures. In addition, several multispectral sensor fusion medical imaging applications were explored including imaging of subcutaneous vasculature, retinal angiography, and endoscopic cholecystectomy. Work is also being performed to advance the state of the art using differential absorption lidar as an active remote sensing technique for spectrally detecting, identifying, and tracking hazardous emissions. These investigations support a wide variety of multispectral signature discrimination applications including the concepts of automated target search, landing zone detection, enhanced medical imaging, and chemical/biological agent tracking.

关键词： detection and tracking algorithms Image fusion Data fusion Sensors Multispectral imaging Target detection Image processing Sensor fusion Medical imaging Missiles

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TRACK ASSOCIATION USING CORRECTION FOR BIAS AND MISSING DATA

TRACK ASSOCIATION USING CORRECTION FOR BIAS AND MISSING DATA

引用

Conference on Signal and Data Processing of Small Targets 1994

作者： BLACKMAN, SS BANH, ND HUGHES AIRCRAFT CO EL SEGUNDOCA 90245

ISBN: (纸本)0819415391

One technique for multisensor tracking forms sensor level tracks using measurements received from the individual sensors. Then, the sensor level tracks are combined into a central level trackfile by performing multisensor track-to-track association and track fusion. Due to difference in sensor resolution, detection capability and coverage, there may be targets for which a track is formed by one sensor but not by the other. Also, tracks formed on the same target by multiple sensors may differ due to multisensor misalignment (or bias) error. This paper addresses these problems by developing a method to perform multisensor track-to-track association under the conditions of intersensor bias and missing track data. An augmentation to the association matrix is developed to account for the face that each sensor may not contain a full set of tracks for all targets in the field of view. An iterative approach is used to estimate and correct for the bias error. Monte Carlo simulation results are presented to illustrate the methods and close correspondence is found between these results and the theoretical probability of correct association.

关键词： Sensors Error analysis Monte Carlo methods detection and tracking algorithms Optical resolution Statistical analysis Target detection Clouds Electro optical sensors Information technology

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BOX CONNECTIVITY APPROACH TO MULTIFONT CHARACTER-RECOGNITION

BOX CONNECTIVITY APPROACH TO MULTIFONT CHARACTER-RECOGNITION

引用

Conference on Document Recognition

作者： KRTOLICA, R CANON RES CTR AMER INC PALO ALTOCA 94304

ISBN: (纸本)081941476X

The idea of box connectivity approach (BCA) is to partition the bounding frame of the character bitmap into a fixed number of rectangles, to define some properties of those rectangles, and to establish connectivity relations between the rectangles. Hamming distance and vector optimization are used for classification. Good results in recognition of high quality data (400 dpi) in three fonts (Courier, Helvetica, and New Times Roman) and eight sizes (from 8 to 24 points) were reported in a previous paper. These findings are confirmed in this paper by an experiment showing that, for the same number of bits, BCA features increase the rate of recognition twice with respect to features obtained by simple decimation. However, the actual method is limited by the fact that the number of referent templates increases with the number of fonts to be recognized. The purpose of this paper is to remove this limitation. The main part of the paper discusses the properties of the Hamming distance and how they can be used in the BCA algorithm to improve the efficiency of classification. The last section reports the results of an experiment showing the discrimination power of BCA features.

关键词： Raster graphics detection and tracking algorithms Optical character recognition Binary data Image classification Algorithm development Antimony Feature extraction Statistical analysis Tin

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NEW BASIS FUNCTION DISTORTION-INVARIANT detection FILTERS 2

NEW BASIS FUNCTION DISTORTION-INVARIANT DETECTION FILTERS

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Conference on Photonics for Processors, Neural Networks, and Memories II

作者： IYER, A CASASENT, D CARNEGIE MELLON UNIV CTR EXCELLENCE OPT DATA PROCDEPT ELECT & COMP ENGNPITTSBURGHPA 15213

ISBN: (纸本)0819416215

New correlation filters for object detection are considered. detection is the first step in general scene analysis. It requires locating the positions of all objects (regions of interest) in a scene. This involves recognizing objects in multiple classes with object distortion and contrast differences in the presence of clutter. To solve this problem, we use basis function descriptions of objects using new Gabor wavelet (CW) filter functions with new correlation plane optimization functions and employ degrees of freedom (DOFs) to satisfy the optimization functions in a controlled manner. We refer to these as DOF filters and to our specific versions as GW-DOF filters.

关键词： Image filtering Distortion Databases Fourier transforms detection and tracking algorithms Linear filtering Optical filters Wavelets Defense and security Wavelet transforms

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COMPARISON OF COHERENT AND NONCOHERENT OPTICAL CORRELATORS 5

COMPARISON OF COHERENT AND NONCOHERENT OPTICAL CORRELATORS

引用

5th Conference on Optical Pattern Recognition

作者： CASASENT, D HOUSE, G CARNEGIE MELLON UNIV DEPT ELECT & COMP ENGNCTR EXCELLENCE OPT DATA PROCPITTSBURGHPA 15213

ISBN: (纸本)0819415413

This paper presents a simplified description of coherent and noncoherent optical correlators and derives the correlator models. The advantages of the tolerances in component positioning and quality for the noncoherent correlator are explained in detail. Performance measures for correlator comparison are outlined and quantitative comparison data are provided. An implementation approach for bipolar noncoherent filters is introduced and promising results simulating a limited number of amplitude and phase levels are given. We will show that the performance of noncoherent and coherent correlators are comparable and thus the noncoherent correlator should be more widely used because of its implementation advantages.

关键词： Optical correlators Image filtering Tolerancing Optical filters Optical pattern recognition detection and tracking algorithms Sensors Image enhancement Lithium Signal to noise ratio

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COMPUTER-AIDED SOLAR ASTRONOMY - AN IMAGE-PROCESSING EXAMPLE 8

COMPUTER-AIDED SOLAR ASTRONOMY - AN IMAGE-PROCESSING EXAMPLE

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8th SPIE Conference on Instrumentation in Astronomy

作者： COLLIN, B ZAVIDOVIQUE, B ETCA CTME CREASYST PERCEPT LABF-94114 ARCUEILFRANCE

ISBN: (纸本)081941493X

In this paper, we describe a complete pattern recognition procedure for extracting magnetic features in solar images, for tracking each feature from an image to another, thus deriving rotational and meridional motions with unequaled accuracy, and for tracking some of these features concurrently within a multispectral image flow, thus building the corresponding 3D magnetic structure and its evolution over time. The segmentation procedures lean upon the `translation' of the physical knowledge into an algorithmic functional decomposition. This methodology enables a fast and robust design of algorithms and leads to a higher accuracy. A multiresolution elastic matching is then used to track features and extract the surface motion of the sun. This matching implies designing an optimization scheme that fits the anisotropy of the motion as well as a target selection that requires no precomputed threshold. The multispectral images are segmented in a cooperative way, thus giving 3D structures. We introduce a fast algorithm to build the 3D connection between planar sections and show how the volumic information is necessary to tracking, based on the same elastic matching scheme.

关键词： Magnetism Image segmentation detection and tracking algorithms Sun 3D image processing Multispectral imaging Image processing Magnetic tracking 3D acquisition Astronomy

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PHOTOTHERMOPLASTIC-BASED CORRELATOR USING NEURAL TRAINING ALGORITHM FOR PATTERN RECOGNITION

PHOTOTHERMOPLASTIC-BASED CORRELATOR USING NEURAL TRAINING AL...

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International Conference on Optical Memory and Neural Networks 94

作者： KISELYOV, BS NOVOSELOV, BA OKONOV, DE RUSSIAN ACAD SCI INST OPT NEURAL TECHNOLMOSCOW 117333RUSSIA

ISBN: (纸本)0819417785

A multichannel correlator based on photothermoplastic is presented in the paper. A one-layer neural network algorithm is realized for pattern recognition. Photothermoplastic holograms efficiency correction is investigated. Neural net learning process is realized using the filters efficiency adjustment. Recognition of the 5 images by 6 recorded feature patterns is shown.

关键词： Neural networks Optical filters detection and tracking algorithms Holograms Optical correlators Electronic filtering Signal detection Holography Pattern recognition Signal processing

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