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

共 335 条记录，以下是231-240 订阅

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FREQUENCY AND ORIENTATION SELECTIVE TEXTURE MEASURES USING LINEAR SYMMETRY AND LAPLACIAN PYRAMID

FREQUENCY AND ORIENTATION SELECTIVE TEXTURE MEASURES USING L...

引用

CONF ON VISUAL COMMUNICATIONS AND image processing 90

作者： BIGUN, J Swiss Federal Institute of Technology (Switzerland)

ISBN: (纸本)0819404217

An efficient, new method for computing texture features based on dominant local orientation is introduced. The features are computed as the Laplacian pyramid is built up. At each level of the Laplacian pyramid, the linear symmetry feature is computed. This feature is anisotropic and estimates the optimal local orientation in the Least Square Error (LSE) sense. This corresponds to the orientation interpolation obtained from the filter responses of a polar gabor decomposition of the local image. The linear symmetry feature consists of two components, the local orientation estimate and its confidence measure based on the error. Since the latter is a measure of evidence for existence of a definite direction, the linear symmetry feature computed as proposed, has the property of orientation selectivity within each frequency channel. The algorithm is based on convolutions with simple separable filters and pixel-wise non-linear arithmetic operations. These properties allow highly parallel implementation, for example on a pyramid machine, yielding real time applications. Experiments based on test images of natural textures are presented.

关键词： image filtering image segmentation Gaussian filters image processing Linear filtering Visual communications Digital filtering Fourier transforms image classification image processing algorithms and systems

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Real time image sequence segmentation using curve evolution

Real time image sequence segmentation using curve evolution

引用

Conference on Real-Time Imaging V

作者： Zhang, J Liu, W Univ Wisconsin Dept Elect Engn & Comp Sci Milwaukee WI 53201 USA

ISBN: (纸本)0819439819

In this paper, we describe a novel approach to image sequence Segmentation and its real-time implementation. This approach uses the 3D structure tensor to produce a more robust frame difference signal and uses curve evolution to extract whole (moving) objects. Our algorithm is implemented on a standard PC running the Windows operating system with video capture from a USB camera that is a standard Windows video capture device. Using the Windows standard video I/O functionalities, our segmentation software is highly portable and easy to maintain and upgrade. In its current implementation on a Pentium 400, the system can perform segmentation at 5 frames/sec with a frame resolution of 160 x 120.

关键词： image segmentation Video Cameras Operating systems Digital filtering Gaussian filters image processing algorithms and systems Video surveillance Motion estimation Video processing

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Melanoma Detection on Dermoscopic images using Superpixels Segmentation and Shape-Based Features 15

Melanoma Detection on Dermoscopic Images using Superpixels S...

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15th International Symposium on Medical Information processing and Analysis (SIPAIM)

作者： Patino, Diego Ceballos-Arroyo, Alberto M. Rodriguez-Rodriguez, Jairo A. Sanchez-Torres, German Branch-Bedoya, John W. Univ Nacl Colombia Sede Medellin Dept Comp & Decis Sci Av 80 65-223 Medellin Colombia Univ Magdalena Fac Engn Cl 32 22-08 Santa Marta Colombia

ISBN: (纸本)9781510634282

In this work, we present a shape-based approach to automatic skin lesion segmentation and classification in dermoscopic images. We aim to differentiate three types of lesion 1) common nevi, 2) atypical nevi, and 3) melanomas by exploring the morphology features of segmented skin lesions. Our method is an attempt to design a computer-aided ABCDEs of melanoma, where the Asymmetry and Border components are estimated using morphological features. The lesions are first segmented using a super-pixel merging strategy with an RGB criterion. Later, the segmentation method was evaluated on the PH2 dataset, and compared with other state-of-the-art skin segmentation methods. The classification was also conducted on the PH2 dataset through a 10-fold cross-validation set-up with a training and testing set partition of 90% and 10% respectively. We employed logistic regression, SVM and a neural network as classification algorithms. The best performances was 86.5% on average with the neural network.

关键词： image segmentation Skin Melanoma Visualization Neural networks Binary data Feature extraction image processing algorithms and systems image classification Skin cancer

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MORPHOLOGICAL ALGORITHM FOR RIDGE EXTRACTION IN FINGERPRINT imageS 4

MORPHOLOGICAL ALGORITHM FOR RIDGE EXTRACTION IN FINGERPRINT ...

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4TH CONF ON image ALGEBRA AND MORPHOLOGICAL image processing

作者： LAKE, C LOUGHEED, R BEYER, J Environmental Research Institute of Michigan (United States)

ISBN: (纸本)0819412791

A common challenge in many image analysis applications is the segmentation of the data into objects of interest (foreground) and background. Typically, the contrast of the data and the background greylevel varies across the image, thereby requiring some form of normalization prior to a threshold step. Previous morphological techniques for data normalization have been quite successful. These approaches include the `rolling ball' of Sternberg and the `top hat' of Serra. These techniques are particularly effective for patterns of interest that are spaced relatively far apart compared to their width. In contrast, the algorithm introduced in this paper is applicable to closely spaced thin broken lines on a highly variable background. Using a combination of greyscale morphology and conditional masking of image data, the approach is shown to be highly robust for closely spaced foreground/background patterns.

关键词： image processing image segmentation Modulation transfer functions image classification Signal processing Databases 3D image processing image analysis image processing algorithms and systems Sensors

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FAST EXTRACTION OF PLANAR SURFACES FROM RANGE imageS

FAST EXTRACTION OF PLANAR SURFACES FROM RANGE IMAGES

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CONF ON APPLICATIONS OF ARTIFICIAL INTELLIGENCE 1993 : MACHINE VISION AND ROBOTICS ( PREPRINTS )

作者： JIANG, XY BUNKE, H Univ. Bern (Switzerland)

ISBN: (纸本)0819412007

In this paper we present a novel technique for rapidly partitioning surfaces in range images into planar patches. Essential for our segmentation method is the observation that in a scan line the points belonging to a planar surface form a straight line segment. Based on this observation, we first divide each scan line into straight line segments and subsequently consider only the set of line segments of all scan lines as segmentation primitives. The principle of our segmentation method is region growing in terms of line segments. We use a noise variance estimation to automatically set thresholds so that the algorithm can adapt to the noise conditions of different range images. The proposed algorithm has been tested on a large number of real range images acquired by two different range sensors. Experimental results show that the proposed algorithm is fast and robust.

关键词： image segmentation Evolutionary algorithms image processing algorithms and systems Artificial intelligence Sensors Digital filtering Information operations image filtering Sun Reconstruction 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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RECOVERING ABSOLUTE DEPTH AND MOTION OF MULTIPLE OBJECTS FROM INTENSITY imageS

RECOVERING ABSOLUTE DEPTH AND MOTION OF MULTIPLE OBJECTS FRO...

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CONF ON STOCHASTIC AND NEURAL METHODS IN SIGNAL processing, image processing, AND COMPUTER VISION

作者： JIANG, F SCHUNCK, BG Univ. of Michigan (United States)

ISBN: (纸本)081940697X

This paper reports an algorithm that recovers absolute depth and motion of multiple objects from intensity images. It has been shown that absolute depth of multiple objects can be recovered from relative normal flows. With normal flows and depth estimated from images, motion recovery becomes a linear regression problem. As the depth estimates can be very noisy, the method of least-median of squares (LMS) is used to robustly recover the object motion. To decompose image points into groups that correspond to independently moving objects, strong-edge points at which normal flows are estimated are grouped into segments. The segments are then grouped into rigidly moving objects if they can be interpreted as such. This algorithm is designed for the case of general motion. However, experiments suggest that rotation makes the estimation of quality normal flows difficult and brings large errors into depth and motion recovery. The algorithm is tested on real images of translating objects.

关键词： image segmentation Cameras Motion estimation image processing algorithms and systems image processing Error analysis Imaging systems Signal processing Stochastic processes Machine vision

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Myocardial Scar Segmentation from Magnetic Resonance images Using Convolutional Neural Network

Myocardial Scar Segmentation from Magnetic Resonance Images ...

引用

Conference on Medical Imaging - Computer-Aided Diagnosis

作者： Zabihollahy, Fatemeh White, James A. Ukwatta, Eranga Carleton Univ Dept Syst & Comp Engn Ottawa ON Canada Univ Calgary Libin Cardiovasc Inst Alberta Calgary AB Canada

ISBN: (数字)9781510616400

ISBN: (纸本)9781510616400

Accurate segmentation of the myocardial fibrosis or scar may provide important advancements for the prediction and management of malignant ventricular arrhythmias in patients with cardiovascular disease. In this paper, we propose a semi-automated method for segmentation of myocardial scar from late gadolinium enhancement magnetic resonance image (LGE-MRI) using a convolutional neural network (CNN). In contrast to image intensity-based methods, CNN based algorithms have the potential to improve the accuracy of scar segmentation through the creation of high-level features from a combination of convolutional, detection and pooling layers. Our developed algorithm was trained using 2,336,703 image patches extracted from 420 slices of five 3D LGE-MR datasets, then validated on 2,204,178 patches from a testing dataset of seven 3D LGE-MR images including 624 slices, all obtained from patients with chronic myocardial infarction. For evaluation of the algorithm, we compared the algorithm-generated segmentations to manual delineations by experts. Our CNN-based method reported an average Dice similarity coefficient (DSC), precision, and recall of 94.50 +/- 3.62%, 96.08 +/- 3.10%, and 93.96 +/- 3.75% as the accuracy of segmentation, respectively. As compared to several intensity threshold-based methods for scar segmentation, the results of our developed method have a greater agreement with manual expert segmentation.

关键词： image segmentation 3D image processing Convolutional neural networks image processing algorithms and systems Algorithm development Magnetic resonance imaging

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NONPARAMETRIC MULTISCALE CURVE SMOOTHING

NONPARAMETRIC MULTISCALE CURVE SMOOTHING

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CONF ON APPLICATIONS OF ARTIFICIAL INTELLIGENCE 1993 : MACHINE VISION AND ROBOTICS ( PREPRINTS )

作者： ROSIN, P Curtin Univ. of Technology (Australia)

ISBN: (纸本)0819412007

Lowe demonstrated a method for automatically segmenting and smoothing image curves by varying degrees. It was intended to remove noise and unnecessary fine detail, aiding subsequent processing such as grouping and matching. An alternative technique is described in this paper that is based on recursively subdividing the curve into alternative sets of sections. Rather than use thresholds on the values of curvature and its derivatives to determine the segmentation and degree of smoothing our technique is driven by three qualitative measures: (1) a criterion for selecting potential breakpoints, (2) a criterion for determining the amount of smoothing for curve sections, and (3) a significance measure that determines which sections form the best selection. The advantages of the technique are robustness, scale invariance, and the absence of parameters.

关键词： Evolutionary algorithms image segmentation Artificial intelligence image processing image processing algorithms and systems Algorithm development Quantization Error analysis Feature extraction Fourier transforms

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Bounding-object segmentation

Bounding-object segmentation

引用

Medical Imaging 2005 Conference

作者： Vetter, M Neuhaus, J Wegner, I Schöbinger, M Meinzer, HP Wolf, I Deutsches Krebsforschungszentrum (Germany)

ISBN: (纸本)0819457213

This paper presents a new method for the semiautomatic segmentation of anatomical or pathological structures in MRI, CT or ultrasound images. The concept of bounding-object segmentation is based on an efficient combination of a new interactive approach with well known automatic segmentation algorithms. The efficiency of this new method is based on the transparent interaction between a 3D scene as well arbitrary 2D views of the scene. Bounding-object segmentation can also be described as a combination of interactive 3D segmentation with region-based, level-set-based, and/or texture based 3D-segmentation algorithms.

关键词： image segmentation Visualization 3D image processing image processing Magnetic resonance imaging Tumors Computed tomography image processing algorithms and systems Kidney Ultrasonography

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