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

共 335 条记录，以下是241-250 订阅

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SEGMENTATION EVALUATION AND COMPARISON - A STUDY OF VARIOUS algorithms

SEGMENTATION EVALUATION AND COMPARISON - A STUDY OF VARIOUS ...

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Meeting on Visual Communications and image Communication 93

作者： ZHANG, YJ DELFT UNIV TECHNOL DEPT APPL PHYSDELFTNETHERLANDS

ISBN: (纸本)0819413690

An objective and quantitative study of several representative segmentation algorithms is presented. In this study, the measurement accuracy of object features from the segmented images is taken to judge the quality of segmentation results and to assess the performance of applied algorithms. Moreover, some synthetic images are specially generated and used in test experiments. This evaluation and comparison study reveals the behavior of those algorithms within various situations, provides their performance ranking under real-like conditions, gives some limits and/or constraints for employing those algorithms in different applications, as well as indicates several potential directions for improving their performance and initiating new developments. Since the investigated algorithms are selected from different technique groups, this study also shows that the presented approach would be valid and effective for treating a wide range of segmentation algorithms.

关键词： image segmentation image processing algorithms and systems Signal to noise ratio Algorithm development Edge detection image processing Detection and tracking algorithms image analysis image filtering Linear filtering

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SUPERVISED INTERPRETATION OF ECHOCARDIOGRAMS WITH A PSYCHOLOGICAL MODEL OF EXPERT SUPERVISION

SUPERVISED INTERPRETATION OF ECHOCARDIOGRAMS WITH A PSYCHOLO...

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CONF ON BIOMEDICAL image processing AND BIOMEDICAL VISUALIZATION

作者： REVANKAR, S SHER, D SHALIN, VL RAMAMURTHY, M SUNY/Buffalo (United States)

ISBN: (纸本)0819411388

We have developed a collaborative scheme that facilitates active human supervision of the binary segmentation of an echocardiogram. The scheme complements the reliability of a human expert with the precision of segmentation algorithms. In the developed system, an expert user compares the computer generated segmentation with the original image in a user friendly graphics environment, and interactively indicates the incorrectly classified regions either by pointing or by circling. The precise boundaries of the indicated regions are computed by studying original image properties at that region, and a human visual attention distribution map obtained from the published psychological and psychophysical research. We use the developed system to extract contours of heart chambers from a sequence of two dimensional echocardiograms. We are currently extending this method to incorporate a richer set of inputs from the human supervisor, to facilitate multi-classification of image regions depending on their functionality. We are integrating into our system the knowledge related constraints that cardiologists use, to improve the capabilities of our existing system. This extension involves developing a psychological model of expert reasoning, functional and relational models of typical views in echocardiograms, and corresponding interface modifications to map the suggested actions to image processing algorithms.

关键词： image segmentation Visualization Heart Human-machine interfaces image analysis image processing Algorithm development Telecommunications image processing algorithms and systems Binary data

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image SEGMENTATION BY WAVELET-BASED AUTOMATIC THRESHOLD SELECTION

IMAGE SEGMENTATION BY WAVELET-BASED AUTOMATIC THRESHOLD SELE...

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Meeting on Visual Communications and image Communication 93

作者： OLIVO, JC EUROPEAN MOLEC BIOL LAB PHYS INSTRUMENTAT PROGRAMMED-69012 HEIDELBERGGERMANY

ISBN: (纸本)0819413690

A segmentation method using a peak analysis algorithm for threshold selection is presented. It is based on the detection of the zero-crossings and the local extrema of a wavelet transform which give a complete characterization of the peaks in the histogram. These values are used for the unsupervised selection of a sequence of thresholds describing a coarse-to-fine analysis of histogram variation. The results of using the proposed technique are presented in the case of different images.

关键词： image segmentation Wavelet transforms Wavelets Smoothing image processing algorithms and systems image resolution Digital filtering Discrete wavelet transforms Signal processing Statistical analysis

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WAVELET-BASED SENSOR FUSION 6

WAVELET-BASED SENSOR FUSION

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CONF ON SENSOR FUSION 6

作者： HUNTSBERGER, T JAWERTH, B Univ. of South Carolina (United States)

ISBN: (纸本)0819413240

Sensor fusion can be performed either on the raw sensor output or after a segmentation step has been done. Our previous work has concentrated on neural network models for sensor fusion after segmentation. Although this method has been shown to be fast and reliable, there is still the overhead entailed from using entire images. The wavelet transform is a multiresolution method that is used to decompose images into detail and average channels. These channels maintain all of the image information and sensor fusion logic operations can be done within the wavelet coefficient space. In addition, image compression can be done within this same space for possible remote transmission. This paper examines sensor fusion within the wavelet coefficient space. The results of some experimental studies performed on the 1024 node NCUBE/10 at the University of South Carolina are also included.

关键词： Wavelets image fusion image segmentation Sensor fusion image compression Wavelet transforms Algorithm development image processing algorithms and systems Logic Sensors

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LOSSY COMPRESSION OF MEDICAL imageS USING PREDICTION AND CLASSIFICATION

LOSSY COMPRESSION OF MEDICAL IMAGES USING PREDICTION AND CLA...

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CONF ON MEDICAL IMAGING 1993 : image CAPTURE, FORMATING, AND DISPLAY

作者： LEE, HS KIM, YM ROWBERG, AH FRANK, MS LEE, WB Univ. of Washington (United States)

ISBN: (纸本)0819411299

In this paper, a lossy image compression algorithm based on a prediction and classification scheme is discussed. The algorithm decomposes an image into four subimages by subsampling pixels at even and odd row and column locations. Since the four subimages have strong correlations to one another, one of them is used in predicting all the others and the resulting differences between the predicted subimages and the original subimages are encoded. Estimated differences tend to be large in a region where pixel values change rapidly, while the differences are small in a monotonous region. This redundancy is explored by dividing the estimated differences into subsets based on the slope of pixel changes, the basis for which is found in some human perception models used to measure the visibility of distortion. The resulting classified estimated differences having different visibilities are encoded with classified vector quantizers.

关键词： image compression image quality image segmentation Distortion Visualization Visibility image classification image processing algorithms and systems Quantization Medical imaging

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ADAPTIVE, MODEL-BASED RESTORATION OF TEXTURES BY GENERALIZED WIENER FILTERING

ADAPTIVE, MODEL-BASED RESTORATION OF TEXTURES BY GENERALIZED...

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Meeting on Visual Communications and image Communication 93

作者： KRISHNAMURTHY, R WOODS, JW FRANCOS, JM RENSSELAER POLYTECH INST DEPT ELECTR COMP & SYST ENGNCTR IMAGE PROC RESTROYNY 12180

ISBN: (纸本)0819413690

We consider the adaptive restoration of inhomogeneous textured images degraded by linear blur and additive white Gaussian noise. The method consists of segmenting the image into individual homogeneous textures and restoring each texture separately. The individual textures are assumed to be realizations of 2-D Wold-decomposition based regular, homogeneous random fields which may possess deterministic components. The conventional Wiener filter assumes that the spectral distribution of the signal is absolutely continuous and, therefore, cannot be directly used to restore the individual textures. A generalized Wiener filter accommodates the unified texture model and is shown to yield minimum mean-squared error estimates for fields with discontinuous spectral distributions. Texture discrimination is performed by obtaining maximum a posteriori estimates for the label field using simulated annealing. The performance of our segmentation algorithm is investigated in the presence of noise.

关键词： Autoregressive models image segmentation Filtering (signal processing) Electronic filtering image restoration image filtering Signal to noise ratio Performance modeling image processing algorithms and systems Visualization

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BOUNDARY DETECTION AND COLOR SEGMENTATION IN SKIN TUMOR imageS

BOUNDARY DETECTION AND COLOR SEGMENTATION IN SKIN TUMOR IMAG...

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CONF ON BIOMEDICAL image processing AND BIOMEDICAL VISUALIZATION

作者： ERCAL, F MOGANTI, M STOECKER, WV MOSS, RH Univ. of Missouri/Rolla (United States)

ISBN: (纸本)0819411388

Boundary detection has been recognized as one of the difficult problems in image processing and pattern analysis, in particular in medical imaging applications. There is no unified approach to this problem which has been found to be application dependent. In this paper, we present a simple and yet effective method to find the borders of tumors as an initial step towards the diagnosis of skin tumors from their color images. The method makes use of an adaptive color metric from red, green, and blue (RGB) planes that contain information to discriminate the tumor from the background. Using this suitable coordinate transformation the image is segmented. The tumor portion is then extracted from the segmented image and borders are drawn. Experimental results which verify the effectiveness of our approach are given.

关键词： Tumors image segmentation Skin image processing image processing algorithms and systems RGB color model Digital filtering image filtering Intelligence systems Molybdenum

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EXTRACTION OF EDGE-BASED AND REGION-BASED FEATURES FOR OBJECT RECOGNITION 12

EXTRACTION OF EDGE-BASED AND REGION-BASED FEATURES FOR OBJEC...

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12th Conference on Intelligent Robots and Computer Vision: algorithms and Techniques

作者： COUTTS, B RAVI, S HU, GZ SHRIKHANDE, N CENT MICHIGAN UNIV DEPT COMP SCIMT PLEASANTMI 48858

ISBN: (纸本)0819413208

One of the central problems of computer vision is object recognition. A catalogue of model objects is described as a set of features such as edges and surfaces. The same features are extracted from the scene and matched against the models for object recognition. Edges and surfaces extracted from the scenes are often noisy and imperfect. In this paper algorithms are described for improving low level edge and surface features. Existing edge extraction algorithms are applied to the intensity image to obtain edge features. Initial edges are traced by following directions of the current contour. These are improved by using corresponding depth and intensity information for decision making at branch points. Surface fitting routines are applied to the range image to obtain planar surface patches. An algorithm of region growing is developed that starts with a coarse segmentation and uses quadric surface fitting to iteratively merge adjacent regions into quadric surfaces based on approximate orthogonal distance regression. Surface information obtained is returned to the edge extraction routine to detect and remove fake edges. This process repeats until no more merging or edge improvement can take place. Both synthetic (with Gaussian noise) and real images containing multiple object scenes have been tested using the merging criteria. Results appeared quite encouraging.

关键词： Edge detection Object recognition image segmentation Algorithm development Feature extraction Detection and tracking algorithms image processing algorithms and systems Computer vision technology Machine vision Visual process modeling

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REGIONAL SHAPE-BASED FEATURE SPACE FOR SEGMENTING BIOMEDICAL imageS USING NEURAL NETWORKS

REGIONAL SHAPE-BASED FEATURE SPACE FOR SEGMENTING BIOMEDICAL...

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CONF ON BIOMEDICAL image processing AND BIOMEDICAL VISUALIZATION

作者： SUNDARAMOORTHY, G HOFORD, JD HOFFMAN, EA Univ. of Iowa Hospitals and Clinics (United States)

ISBN: (纸本)0819411388

In biomedical images, structure of interest, particularly the soft tissue structures, such as the heart, airways, bronchial and arterial trees often have grey-scale and textural characteristics similar to other structures in the image, making it difficult to segment them using only gray- scale and texture information. However, these objects can be visually recognized by their unique shapes and sizes. In this paper we discuss, what we believe to be, a novel, simple scheme for extracting features based on regional shapes. To test the effectiveness of these features for image segmentation (classification), we use an artificial neural network and a statistical cluster analysis technique. The proposed shape-based feature extraction algorithm computes regional shape vectors (RSVs) for all pixels that meet a certain threshold criteria. The distance from each such pixel to a boundary is computed in 8 directions (or in 26 directions for a 3-D image). Together, these 8 (or 26) values represent the pixel's (or voxel's) RSV. All RSVs from an image are used to train a multi-layered perceptron neural network which uses these features to 'learn' a suitable classification strategy. To clearly distinguish the desired object from other objects within an image, several examples from inside and outside the desired object are used for training. Several examples are presented to illustrate the strengths and weaknesses of our algorithm. Both synthetic and actual biomedical images are considered. Future extensions to this algorithm are also discussed.

关键词： image segmentation image processing algorithms and systems Neural networks Biomedical optics image classification Feature extraction Distance measurement 3D image processing Computed tomography Visualization

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SEQUENTIAL COMPUTER algorithms FOR PRINTED-CIRCUIT BOARD INSPECTION 12

SEQUENTIAL COMPUTER ALGORITHMS FOR PRINTED-CIRCUIT BOARD INS...

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12TH CONF ON INTELLIGENT ROBOTS AND COMPUTER VISION : ACTIVE VISION AND 3D METHODS

作者： HERNANDEZ, ME VILLALOBOS, JR JOHNSON, WC Univ. of Texas/El Paso (United States)

ISBN: (纸本)0819413216

Surface mounted technology (SMT) in automated assembly facilities requires the use of automatic surface-mount-device (SMD) placement machines. One of the problems involved in the electronic printed circuit board (PCB) assembly process is the verification of the SMD placement operation within tight tolerances. The high throughput of modern manufacturing lines along with the required accuracy demand the use of automatic inspection systems to verify SMD placement. image complexity of the board makes the use of machine vision for the inspection process a difficult task. This is complicated by the fact that misclassification errors should be kept to a minimum. Additionally, it is desirable that the inspection results provide enough information to be used for statistical process control (SPC). The strategy adopted to solve this problem was to simplify the complexity of the image by means of special illumination devices. The simplified image was then suitable for analysis by simple processing, segmentation, and detection algorithms that, sequentially applied to the image, met the required repeatability and accuracy specifications for the inspection system. The scope of this paper is to describe the techniques explored by the authors to solve the SMD inspection problem in order to develop a working industrial SMD inspection system.

关键词： Inspection Machine vision image segmentation image processing Computer vision technology Robot vision Robots Light emitting diodes Detection and tracking algorithms image processing algorithms and systems

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