Showing papers on "Image segmentation published in 1982"
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TL;DR: A new technique for matching image features to maps or models which forms all possible pairs of image features and model features which match on the basis of local evidence alone and which is robust with respect to changes of image orientation and content.
Abstract: A new technique is presented for matching image features to maps or models. The technique forms all possible pairs of image features and model features which match on the basis of local evidence alone. For each possible pair of matching features the parameters of an RST (rotation, scaling, and translation) transformation are derived. Clustering in the space of all possible RST parameter sets reveals a good global transformation which matches many image features to many model features. Results with a variety of data sets are presented which demonstrate that the technique does not require sophisticated feature detection and is robust with respect to changes of image orientation and content. Examples in both cartography and object detection are given.
304 citations
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TL;DR: By modeling a picture as a two-state Markov field, MAP estimation techniques are used to develop sub-optimal but computationally tractable binary segmentation algorithms as discussed by the authors.
98 citations
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01 Sep 1982
TL;DR: This paper investigates several variations on the basic linking process with regard to such factors as initialization, criteria for linking, and iteration scheme used and extends the approach to links based on more than one feature of a pixel, e.g., on color components or local property values.
Abstract: A recently developed method of image smoothing and segmentation makes use of a "pyramid" of images at successively lower resolutions. It establishes links between pixels at successive levels of the pyramid; the subtrees of the pyramid defined by these links yield a segmentation of the image into regions over which the smoothing takes place. This paper investigates several variations on the basic linking process with regard to such factors as initialization, criteria for linking, and iteration scheme used. It also studies generalizations in which the links are weighted rather than forced, and in which interactions among the pixels at a given level are also allowed. Finally, it extends the approach to links based on more than one feature of a pixel, e.g., on color components or local property values.
71 citations
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TL;DR: This paper studies some of the problems that arise with linked-pyramid segmentation, and proposes a two-stage segmentation process that overcomes these problems.
67 citations
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TL;DR: A simple class of piecewise constant approximations to an image is constructed as follows: start with the entire image, subdivide it into quadrants if its gray level standard deviation is high, and repeat the process for each quadrant so that each of them can be approximated by a constant value, namely, its mean.
Abstract: A simple class of piecewise constant approximations to an image is constructed as follows: start with the entire image, subdivide it into quadrants if its gray level standard deviation is high, and repeat the process for each quadrant. This yields a decomposition of the image into blocks, each having low standard deviation, so that each of them can be approximated by a constant value, namely, its mean. The histogram of this approximated image tends to have sharper peaks than that of the original image since the block averaging reduces the variability of the gray levels within homogeneous regions. A possible way of further improving the histogram is based on the fact that small blocks tend to occur near region borders; thus, suppressing these blocks should tend to deepen the valleys on the histogram, making threshold selection (to separate regions of different types) easier. Conversely, the histogram of the small blocks only represents a population of pixels near region borders, and if there are only two types of regions (e.g., objects and background), the mean of this histogram should be a useful threshold for separating them; but in practice, this method is not very reliable since background fluctuations also give rise to border pixels.
65 citations
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TL;DR: The tracking algorithm is implemented to track moving objects with occasional occlusion in computer-simulated binary images and a variational estimation algorithm is developed to track the dynamic parameters of the operators.
Abstract: A mathematical model using an operator formulation for a moving object in a sequence of images is presented. Time-varying translation and rotation operators are derived to describe the motion. A variational estimation algorithm is developed to track the dynamic parameters of the operators. The occlusion problem is alleviated by using a predictive Kalman filter to keep the tracking on course during severe occlusion. The tracking algorithm (variational estimation in conjunction with Kalman filter) is implemented to track moving objects with occasional occlusion in computer-simulated binary images.
62 citations
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TL;DR: A gradient relaxation method based on maximizing a criterion function is studied and compared to the nonlinear probabilistic relaxation method for the purpose of segmentation of images having unimodal distributions.
Abstract: A gradient relaxation method based on maximizing a criterion function is studied and compared to the nonlinear probabilistic relaxation method for the purpose of segmentation of images having unimodal distributions. Although both methods provide comparable segmentation results, the gradient method has the additional advantage of providing control over the relaxation process by choosing three parameters which can be tuned to obtain the desired segmentation results at a faster rate. Examples are given on two different types of scenes.
53 citations
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03 May 1982TL;DR: Ohlander et al. as discussed by the authors discussed issues of recursive region segmentation in the context of PHOENIX, the newest version of region segmentations, running on a VAX 11/780 under UNIX.
Abstract: Recursive segmentation of an image into regions using histograms is one of the most widely used techniques for image segmentation. At CMU, several versions of a region segmentation program have been developed based on this technique (Ohlander, Price, Shafer and Kanade). Based on these experiences, this paper discusses issues of recursive region segmentation in the context of PHOENIX, the newest version of region segmentation program, running on a VAX 11/780 under UNIX. The issues discussed in this paper include: Image features to be used in histogramming; comparison of the algorithm with other techniques; important improvements made in PHOENIX over its predecessor (Ohlander and Price); and some inherent problems in histogram-based segmentation together with suggestions for minimizing them. PHOENIX is being incorporated into the ARPA Image Understanding Testbed, under construction at SRI International.
43 citations
01 Jan 1982
TL;DR: The methodologies and capabilities of image segmentation techniques are reviewed and single linkage schemes, centroid linkage scheme, histogram mode seeking, spatial clustering, and split and merge schemes are addressed.
Abstract: The methodologies and capabilities of image segmentation techniques are reviewed. Single linkage schemes, hybrid linkage schemes, centroid linkage schemes, histogram mode seeking, spatial clustering, and split and merge schemes are addressed.
42 citations
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TL;DR: A technique for locating desired structures utilizing user specified information about properties of these structures and their relationships with other more easily extracted objects is described and results of the processing of aerial pictures are presented.
Abstract: A technique for locating desired structures utilizing user specified information about properties of these structures and their relationships with other more easily extracted objects is described. An edge-based and region-based technique is used for scene segmentation. Experimental results of the processing of aerial pictures are presented.
41 citations
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TL;DR: A hybrid “split-and link” approach that combines features of both the split-and-merge and the overlapped “pyramid” approaches to segmentation is proposed.
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TL;DR: In this article, an image segmentation algorithm based on histogram clustering and probabilistic relaxation labeling is explored by means of a set of artificially generated test images with known parameters.
Abstract: An image segmentation algorithm based on histogram clustering and probabilistic relaxation labeling is explored. The algorithm is evaluated by means of a set of artificially generated test images with known parameters. Two sources of pixel labeling errors are revealed. The first derives from distribution overlap in the histogram and leads to fragmented or missing regions in a segmentation. The second derives from the gloal nature of the compatibility coefficients used in the relaxation process. The coefficients are shown to be insufficient to correct certain labeling errors and can even cause the destruction of fine image details during the course of the relaxation updating process. A potential solution to these problems is shown to be obtainable by using orientation dependent compatibility coefficients and localizing the scope of the algorithm to small subimages followed by a merging of the segmented subimages.
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TL;DR: This correspondence provides some theoretical aspects of the problem of picture segmentation that are practically unsolvable in its more general case formulation.
Abstract: The problem of picture segmentation is widely believed to be practically unsolvable in its more general case formulation. However, as far as the authors know no formal argumentation has yet been given to this belief related to the segmentation problem. This correspondence provides some theoretical aspects of this phenomenon.
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01 May 1982TL;DR: A new image coding technique, based on a simplified description of a region-composed image, which uses an adaptive psychovisually oriented segmentation process to achieve promising results in data compression.
Abstract: A new image coding technique, based on a simplified description of a region-composed image is presented. The regions are extracted from the original image by an adaptive psychovisually oriented segmentation process. The picture elements (pels) inside the regions represent the texture information of the image whereas the region boundaries points represent the contour information. The data-adaptive character of this method as well as the use of some psychovisual characteristics of the human visual system lead to promising results in data compression.
01 Dec 1982
TL;DR: This report summarizes application for which PHOENIX is suited, the history and nature of the algorithm, details of the Testbed implementation, the manner in which PH oenIX is invoked and controlled, the type of results that can be expected, and suggestions for further development.
Abstract: : PHOENIX is a computer program for segmenting images into homogeneous closed regions. It uses histogram analysis, thresholding and connected-components analysis to produce a partial segmentation, then resegments each region until various stopping criteria are satisfied. Its major contributions over other recursive segmenters are a sophisticated control interface, optional use of more than one histogram-dependent intensity threshold during tentative segmentation of each region. and spatial analysis of resulting subregions as a form of "look-ahead" for choosing between promising spectral features at each step. PHOENIX was contributed to the DARPA Image Understanding Testbed at SRI by Carnegie-Mellon University. This report summarizes application for which PHOENIX is suited, the history and nature of the algorithm, details of the Testbed implementation, the manner in which PHOENIX is invoked and controlled, the type of results that can be expected, and suggestions for further development. Baseline parameter sets are given for producing reasonable segmentations of typical imagery.
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01 May 1982TL;DR: It is shown how the techniques of Digital Image Analysis can be efficiently used in the interpretation of seismic cross-sections to cope with the characteristics of seismic signals.
Abstract: We show how the techniques of Digital Image Analysis can be efficiently used to help in the interpretation of seismic cross-sections. The problem of automatically finding homogeneous facies is in fact directly tied to Image Processing problems such as edge detection, texture analysis, segmentation and classification. We briefly overview some existing tools, outline some new techniques which had to be invented to cope with the characteristics of seismic signals and demonstrate on many examples the power of our approach.
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TL;DR: An image can be segmented by classifying its pixels using local properties as features, and two intuitively useful properties are the gray level of the pixel and the ``busyness,'' or gray level fluctuation, measured in its neighborhood.
Abstract: An image can be segmented by classifying its pixels using local properties as features. Two intuitively useful properties are the gray level of the pixel and the ``busyness,'' or gray level fluctuation, measured in its neighborhood. Busyness values tend to be highly vari-able in busy regions; but great improvements in classification accuracy can be obtained by smoothing these values prior to classifying. An alternative possibility is to classify probabilistically and use relaxation to adjust the probabilities.
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TL;DR: This correspondence describes a moving target tracking (MTT) algorithm that performs image registration and motion analysis between pairs of images from a passive sensor.
Abstract: This correspondence describes a moving target tracking (MTT) algorithm that performs image registration and motion analysis between pairs of images from a passive sensor. Unlike previously reported moving target indicators that operate at the signal level, the registration and motion analysis in the MTT is totally performed at a symbolic level. The operation of the MTT is demonstrated by simulation results obtained from applications of the algorithm to infrared images.
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TL;DR: A machine vision system for automatic characterization of sections of biopsied tissue capable of recognizing normal liverBiopsies and liver biopsies showing alcoholic hepatitis and acute viral hepatitis is described.
Abstract: This paper describes a machine vision system for automatic characterization of sections of biopsied tissue. Color images are first segmented by using an original color segmentation procedure. A structural analysis is then performed over the segmented images to extract the same features that a pathologist would use to make a diagnosis. Alternatively, monochromatic images can be analyzed by using cellular logic techniques. These two methods were used to implement a machine vision system capable of recognizing normal liver biopsies and liver biopsies showing alcoholic hepatitis and acute viral hepatitis. The color segmentation procedure leads to 100 percent classification success in distinguishing between the normal and acute viral hepatitis classes. By using cellular logic techniques, no overlap was found between the normal, acute viral hepatitis, and alcoholic hepatitis classes at the 90 percent confidence interval.
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04 Nov 1982TL;DR: In this article, the optical effects of segment phasing errors are derived, showing that at least for visible light observations the phasing is not important, and a general relation between surface quality and image quality is given, and the implications for surface quality tolerances are discussed.
Abstract: A number of designs for future astronomical telescopes call for large primary mirrors that are mosaics of smaller mirrors. We describe here a study of some characteristics of the images expected from a telescope with a primary mirror composed of 36 hexagonal segments. Various effects caused by the segmentation and imperfections in the segment fabrication and control have been analyzed using physical optics. The diffraction-limited image distribution from the segmentation geometry of the primary is derived, and the diffraction spikes are shown to be similar to those caused by secondary support struts in existing telescopes. A general relation between surface quality and image quality is given, and the implications for surface quality tolerances are discussed. The optical effects of segment phasing errors are derived, showing that at least for visible light observations the phasing is unimportant. For observations at 10 μm near diffraction-limited perfor-mance can be achieved with a 10 meter aperture requiring that the segments be phased correctly at this wavelength.© (1982) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
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01 May 1982TL;DR: By modelling a picture as a two-state Markov field, MAP estimation techniques are used to develop suboptimal but computationally tractable binary segmentation algorithms.
Abstract: By modelling a picture as a two-state Markov field, MAP estimation techniques are used to develop suboptimal but computationally tractable binary segmentation algorithms.
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TL;DR: A new simple and robust segmentation method which combines the advantages of both the classical edge and region approaches is introduced, which uses the inherent property of edges to provide transition thresholds between regions of monotonous intensity.
Abstract: Aiming at designing the image processing unit of a visual prosthesis for sight handicapped, an efficient picture simplification scheme for tactile outputs is proposed. Some psychological considerations are given to help in its development. A new simple and robust segmentation method which combines the advantages of both the classical edge and region approaches is introduced. This method uses, on the one hand, the inherent property of edges to provide transition thresholds between regions of monotonous intensity, and on the other hand, the fact that region segmentation methods give closed regions. A region labeling is applied using those thresholds, yielding well outlined areas. Artificial textures are introduced to help in the tactile discrimination of shapes.
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TL;DR: The algorithm, named MITES, represents an alternative to the traditional pixel classification approach to texture image segmentation because it makes explicit use of the spatial coherence of uniformly textured regions.
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01 Nov 1982TL;DR: An algorithm based on a-priori assumptions about a cell's shape and size and works on one object at a time, capable of verifying that the isolated object really looks like a cell; an essential feature in an automatic system.
Abstract: A correct segmentation of cell images intonucleus, cytoplasm and background is a prerequi- site for a working automatic pre- screening devicefor cervical cytology. This paper presents an al- gorithm for determining the segmentation thres-holds. It is based on a- priori assumptions about a cell's shape and size and works on one object at a time, disregarding everything else in the image.The algorithm is capable of verifying that theisolated object really looks like a cell; an es-sential feature in an automatic system. The nu-cleus and cytoplasm thresholds are decided upon almost independently of each other. The algorithmworks by tracking iso- density contours around theobject to be isolated and its execution time is thus proportional to the length of the contourrather than the area of the image. Some prelimi-nary results are given and the possibility of ef-ficiently implementing the algorithm in hardwareis discussed.INTRODUCTION A lot of effort has been put into the re-search towards an automated cervical pre- screeningdevice based on image processing. One reason whythese attempts so far
01 Sep 1982
TL;DR: In this article, a pyramid of successively reduced-resolution versions of the image is used to define link strengths between pairs of pixels at successive levels of this pyramid, based on proximity and similarity, and iteratively recomputes the pixel values and adjusts the link strengths.
Abstract: : This paper describes a method of image segmentation that creates a partition of the image into compact, homogeneous regions using a parallel, iterative approach that does not require immediate forced choices. The approach makes use of a 'pyramid' of successively reduced-resolution versions of the image. It defines link strengths between pairs of pixels at successive levels of this pyramid, based on proximity and similarity, and iteratively recomputes the pixel values and adjusts the link strengths. After a few iterations, the link strengths stabilize, and the links that remain strong define a set of subtrees of the pyramid. Each such tree represents a compact (piece of a ) homogeneous region in the image; the leaves of the subtree are the pixels in the region, and the size of the region depends on how high the root of the tree lies in the pyramid. Thus the trees define a partition of the image into (pieces of) homogeneous regions.
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TL;DR: This chapter focuses on structural methods in image analysis and recognition, which allow the designer or the user of a pattern recognition system to employ a somewhat intuitive description of an object as the basis for a recognition scheme.
Abstract: Publisher Summary A wide variety of techniques has been developed for image analysis. One common approach consists of image segmentation using some type of similarity criterion for grouping areas within an image followed by measurement of resulting region properties such as shape and texture. These measurements are used to classify the regions into types by computing the similarity of these measurements to those of a set of tracking regions. Statistical methods such as discriminant analysis and the Bayesian classifiers have been used for this classification step. This chapter focuses on structural methods in image analysis and recognition. The primary goal of structural pattern recognition procedures has been the recognition of objects in an image. Structural methods are appealing because they allow the designer or the user of a pattern recognition system to employ a somewhat intuitive description of an object as the basis for a recognition scheme. A fundamental part of many structural recognition systems is a search space. This space may be explicitly stored in a computer or implicitly stored and dynamically generated as in a grammar. Often measures of merit are defined on those parts of the search space that have been examined.
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01 May 1982TL;DR: It is shown that one of the key problems in Image Understanding is the matching of two symbolic structures, a model and the result of a segmentation and a formalism is presented which can deal with the inexact or fuzzy matching of such structures in a highly parallel fashion.
Abstract: We show that one of the key problems in Image Understanding is the matching of two symbolic structures, a model and the result of a segmentation. These symbolic structures are conveniently represented as labeled graphs and we present on two examples a formalism which can deal with the inexact or fuzzy matching of such structures in a highly parallel fashion.
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20 Jan 1982
TL;DR: In this article, the authors propose to get rid of a restriction of a format of a graphic form on a recording medium, by outputting the information of the graphic form only within a range which has been partitioned by a discrimination mark on the recording medium in an image data segmentation device.
Abstract: PURPOSE:To get rid of a restriction of a format of a graphic form on a recording medium, by outputting the information of a graphic form only within a range which has been partitioned by a discrimination mark on the recording medium, in an image data segmentation device. CONSTITUTION:A graphic form which is required for storing the graphic information in a disk memory device is recorded only within rectangular ranges 2, 3 of a slip 1. In order to decide said ranges 2, 3, discrimination marks a2b2c2d2, a3b3c3d3 are printed in advance. On an image segmentation device is provided a discrimination mark recognition part for recognizing the discrimination marks a2b2c2d2, a3b3c3d3 in a graphic form from the graphic information, and in accordance with a signal from this recognition part, graphic information of only the part within the range which has been partitioned by the discrimination mark is segmented and is outputted.