Showing papers on "Distance transform published in 1992"

Distance field manipulation of surface models

Abstract: A surface manipulation technique that uses distance fields-scalar fields derived geometrically from surface models-to combine, modify, and analyze surfaces is presented. It is intended for application to complex models arising in scientific visualization. Computing distance from single triangles is discussed, and an optimized algorithm for computing the distance field from an entire closed surface is built. The use of the fields for surface removal, interpolation and blending is examined. The strength of the approach is that it lets simple 3D algorithms substitute for potentially very complex 2D methods. >

Acceleration of ray-casting using 3-D distance transforms

Abstract: This paper introduces a novel approach for speeding up the ray casting process commonly used in volume visualization methods This new method, called Ray Acceleration by Distance Coding, RADC for short, uses a 3D distance transform to determine the minimum distance to the nearest interesting object; the implementation of a fast andaccurate distance transform is described in detail High distance values, typically found at off-center parts of thevolume, cause many sample points to be skipped, thus significantly reducing the number of samples to be evaluatedduring the ray casting step The minimum distance values that are encountered while traversing the volume can be used for the identification of rays that do not hit objects Our experiments indicate that the RADC method can reduce the number of sample points by a factor between 5 and 20 1 INTRODUCTION In spite of the rapidly increasing computational power of modern workstations, interactive rendering of volumetricdatasets still poses tremendous problems due to the sheer amount of data that must be processed Although parallelcomputer architectures as Pixel Planes 51

Comparing images using the Hausdorff distance under translation

Abstract: Efficient algorithms are provided for computing the Hausdorff distance between a binary image and all possible relative positions (translations) of a model, or a portion of that model. The computation is in many ways similar to binary correlation. However, it is more tolerant of perturbations in the locations of points because it measures proximity rather than exact superposition. >

Distance measuring method and a distance measuring apparatus

Abstract: Method and apparatus for obtaining distance data from an object to a lens by obtaining an image of the object by an image input unit for forming an image of the object through the lens on an image receiving plane. Two observed images Is and Is' with different blurs from the image input unit are obtained by making a position of the lens and/or a position of the image receiving plane with regard to the object different by a minute distance Δz. A filtering process is then performed by applying a filter to the two input observed images Is and Is', thereby providing two output images Fs and Fs'. The distance a up to the object is calculated by using the two output images Fs and Fs' obtained by the filtering process based on the relation between the two output images Fs and Fs' and radius s of the blur and the distance a from the lens to the object.

A mathematical morphology approach to Euclidean distance transformation

Abstract: A distance transformation technique for a binary digital image using a gray-scale mathematical morphology approach is presented. Applying well-developed decomposition properties of mathematical morphology, one can significantly reduce the tremendous cost of global operations to that of small neighborhood operations suitable for parallel pipelined computers. First, the distance transformation using mathematical morphology is developed. Then several approximations of the Euclidean distance are discussed. The decomposition of the Euclidean distance structuring element is presented. The decomposition technique employs a set of 3 by 3 gray scale morphological erosions with suitable weighted structuring elements and combines the outputs using the minimum operator. Real-valued distance transformations are considered during the processes and the result is approximated to the closest integer in the final output image. >

A unified distance transform algorithm and architecture

Abstract: Standard distance transform algorithms produce approximate results and are unsuitable for real-time implementation since they require massive parallelism. A new unified algorithm that computes distance and related nearest feature transforms concurrently for arbitrary bit maps based on any distance function from a broad class is presented. The algorithm has an efficient implementation on serial processors and a unified transform architecture is proposed for feasible real-time performance based on parallel row followed by parallel column scanning. Its importance lies in that it supports real-time performance and a broader set of machine vision applications than the standard approach.

Chamfer masks: discrete distance functions, geometrical properties and optimization

Abstract: The chamfer distances are based on the definition of masks whose size can change depending on the quality of the approximation which is expected, compared to the Euclidean distance. The authors show the induced geometrical properties of the generated distance images, and calculate the required properties of the mask to ensure that they define a distance function. Then they show how to optimize the masks directly in discrete space, and finally, present some main applications. >

Using Force Fields Derived from 3D Distance Maps for Inferring the Attitude of a 3D Rigid Object

Abstract: This paper presents a new method for evaluating the spatial attitude (position-orientation) of a 3D object by matching a 3D static model of this object with sensorial data describing the scene (2D projections or 3D sparse coordinates). This method is based on the pre-computation of a force field derived from 3D distance maps designed to attract any 3D point toward the surface of the model. The attitude of the object is infered by minimizing the energy necessary to bring all of the 3D points (or projection lines) in contact with the surface (geometric configuration of the scene). To quickly and accurately compute the 3D distance maps, a precomputed distance map is represented using an octree spline whose resolution increases near the surface.

Distance measuring apparatus utilizing two-dimensional image

Abstract: A distance measuring apparatus which can accurately measure the distance to an object and keep track of the object. In the apparatus, a pair of image-pickup optical systems pick up an object. A window including the object is set in an image picked up by one of the image-pickup optical systems. The distance to the object is measured by calculating correlation between the image in the window and an image picked up by the other image pickup optical system. Tracking an object is also possible by taking a correlation of images in the window formed in a time sequence. Adequate exposure is determined from an image signal in the window so that the image pickup optical systems are controlled to set the adequate exposure to the image in the window. Contrast of an image in the window becomes distinct, thus enabling accurate distance calculations and tracking of an object.

Nonsupervised 3D registration of PET and MRI data using chamfer matching

Abstract: An extension of the chamfer matching technique to accurately register 3-D medical images from different modalities is proposed. A shape-independent surface matching technique yields a rigid body transformation, which allows the transfer of information between modalities. The optimal transformation is inferred from the minimization of a quadratic generalized distance between discrete surfaces. The minimization process is efficiently performed via the precomputation of a 3-D distance map. The entire registration process requires no supervision. The accuracy of the proposed unsupervised 3-D registration method turned out to be very satisfactory for PET (positron emission tomography) medical studies. >

Method and apparatus for constructing three-dimensional surface shading image display

Abstract: A method and an apparatus for constructing three-dimensional surface shading image display from three-dimensional sequential tomographic images, capable of obtaining the distance image at a high speed by using a hardware configuration with a high general applicability. In the apparatus, an individual distance image for each of the tomographic images with respect to a predetermined reference plane is constructed; a synthesized distance image in which the individual distance images for all of the tomographic images are synthesized together is constructed, by sequentially carrying out an image extrema calculation between each individual distance image for each tomographic image and a previous synthesized distance image; a distance image for surface shading is constructed by applying an affine transformation to the synthesized distance image; and a surface shading image is obtained by applying a shading process to the distance image for surface shading. The image extrema calculation can be either an image minima calculation or an image maxima calculation.

Combining shape-based and gray-level interpolations

Abstract: Sectional images generated by medical scanners usually have lower interslice resolution than resolution withinthe slices. Shape-based interpolation is a method of interpolation that can be applied to the segmented 3Dvolume to create an isotropic data set. It uses a distance transform applied to every slice prior to estimationof intermediate binary slices. Gray-level interpolation has been the classical way of estimating intermediateslices. The method reported here is a combination of these two forms of interpolation, using the local gradientas a normalizing factor of the combination. Overall, this combination of the methods performs better thaneither of them applied individually. 1. INTRODUCTION Three-dimensional data created by tomographic medical imaging devices are usually presented as a sequenceof two-dimensional slices. The distance between the slices is typically greater than the distance between thepixels within the slices. An interpolation technique is often applied to convert the data to an isotropic volumewith the same resolution in all three dimensions. Interpolation is also necessary for accurate quantitative

Distance between images

Abstract: The authors compare two methods which compute an approximation to the Hausdorff distance between pairs of binary images. They also implement a parallel vision of one of the methods, which can provide a fast image distance algorithm to calibrate algorithms performing such tasks as image recognition, image compression, or image browsing. For this purpose, they have shown a simple application of selecting the best iteration of a region growing algorithm which yields edge images by comparing them to a Canny edge detector. >

Towards representation of 3D shape: global surface parametrization

Abstract: A procedure for the parametrization of the surface of a simply connected object is presented. Starting from a relational data structure describing surface nodes and links to edges and vertices, a distance transform is applied to determine two distant poles. The physical model of a heat conducting surface is then used to obtain latitude and longitude parameters. The net created assigns a unique coordinate pair to each surface node, but its structure depends on the selection of the poles and comprises a systematic nonuniformity of node distributions over the sphere. To correct distortions and to achieve independence of starting conditions, an isotropic non-linear relaxation of the node locations on the sphere is developed. This dynamic modelling procedure is used to obtain the final parametrization.

Computer recognition of hand-written characters using the distance transform

Abstract: A new statistical classifier for hand-written character recognition is presented. The system features a preprocessing phase for image normalisation and a distance transform applied to the normalised image, which converts a B/W picture into a grey scale image. A k-nearest-neighbour classifier follows, based on the distance transform and a suitable metric. The system has an accuracy of 98.96% when applied to the US Post Office zip code database, at 0.98% error rate.

Inter-vehicle distance measuring device

Abstract: An inter-vehicle distance measuring device which can automatically set a tracing window for tracing an image of a fore-running vehicle to be measured for distance. One of the images is obtained by image sensors (3, 4) and when they pick up an image of a fore-running vehicle (5) through lenses (1, 2). A window setting unit (12) sets plural number of windows at given locations on the one of the images. An estimate member calculates a distance up to objects caught by those windows, detects the symmetry of the image, and estimates presence of a fore-running vehicle and its position on one of images, and the detected distance data as well. A tracing window is automatically set at the position.

Skeletonisation as model based feature detection

Abstract: Two closely related methods for skeletonisation via a Euclidean distance transform are presented. Firstly, from an observation on the response of the human visual system to a grey level image of the transform, convolution with the Marr Hildreth operator is proposed. Secondly, it is suggested that skeletonisation can be performed by convolution of the distance transform with a function designed to detect the occurrence of a specific geometric model or feature, in a way similar to that used in contemporary edge detection algorithms. Examples of the technique are shown and the results discussed. >

On-vehicle outside monitoring device

Abstract: PROBLEM TO BE SOLVED: To efficiently eliminate noise included in distance images, to improve a space resolution in the position detection of an object and to provide more precise and highly reliable outside world information. SOLUTION: In a computer 30 for an image processing, the distance images from an image processor 20 are read, data above a road surface are selected from the distance images based on a detected road shape, the distance images are divided into the groups of the almost same picture element shift number by a group filtering processing and the ones present at a position higher than the road surface for which the area of a group is larger than a threshold value among distance picture elements are extracted as three-dimensional object data. Then, when the images are sectioned with prescribed intervals in left and right directions, the three-dimensional object data are classified for respective sections and a histogram is prepared, the position where a degree becomes more than the threshold value or the position where the degree becomes maximum in a shortest distance is detected and the position is defined as the distance of a three-dimensional object of the section. Thus, false data by the noise or the like are eliminated and mismatching is prevented. COPYRIGHT: (C)1998,JPO

On Motion Estimation For A Mobile Robot Navigating In Natural Environment: Matching Laser Range Measurements Using The Distance Transform

Abstract: The goal behind this paper is to find a generic method for controlling the motion of a robot relative to an object of an arbitrary shape. In this paper we study; - modelling laser range measurement ...

Automatic feature extraction using data fusion in remote sensing

Abstract: This paper presents two examples of low level strategies using multisensor data fusion, one for bridge extraction, and one for urban area extraction. These extractions are made front a couple of coregistred Synthetic Aperture Radar (SAR) and SPOT images. These features are very different by their dimensions, their shape, and their radiometry. So we C1U prove the reliability of our approach on many types of features. Our method uses the notion of complementarity of each sensor, and the notion of context in the observed scene. For bridge detection, we first segment water in the SPOT image, to spatially constrain the bridge research in the SAR image. This research is achieved using a correlation method. To detect an urban area, we first use the knowledge that it produces very bright texture in SAR imagery. Thus, the main part of urban backscatters is extracted using an adaptative thresholding which keeps the upper band of the gray level histogram of the SAR image. This mask is then used for classification as a training set using a distance map of urban area texture in SPOT image. We determine the non urban zone training set using a distance map of the urban training zone boundaries. Classification is performed with multivariate Gaussian classifier. The results we obtained are very encouracting, especially if we consider the robustness of the bridge detection method.© (1992) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Method and device for processing distance image

Abstract: PURPOSE:To eliminate necessity for previously specifying relation between a coordinate system, where an object is positioned, and the coordinate system of an image. CONSTITUTION:This distance image processing method is provided with a process (S303) to transform the form of an inputted distance image and to normalize it with respect to respective axes, arithmetic process (S306, 308, 317, 319, 321, 323 and 325) to prepare data expressing the character of an object surface described by the distance image by calculating the value of the transformed distance image, and display process (S322, 324 and 326) to display image information expressing the character of the object surface based on the data prepared by the arithmetic process.

Parallel Algorithms for the Distance Transformation

Abstract: The distance transformation (DT) is a basic operation in image analysis where it is used for object recognition A DT converts a binary image consisting of foreground pixels and background pixels, into an image where all background pixels have a value equal to the distance to the nearest foreground pixel

A Mathematical Morphology Approach Distance Transformation

Abstract: This paper presents a distance transformation technique for a binary digital image using a gray scale mathe- matical morphology approach. A distance transformation con- verts a binary image which consists of object (foreground) and nonobject (background) pixels into an image where every ob- ject pixel has a value corresponding to the minimum distance from the background. The distance computation is, in fact, a global operation. Morphological erosion is an operation which selects the minimum value from the combination of an image and the predefined weighted structuring element within a win- dow. Hence, mathematical morphology is the most appropriate approach to distance transformation. Applying well-developed decomposition properties of mathematical morphology, we can significantly reduce the tremendous cost of global operations to that of small neighborhood operations suitable for parallel pipelined computers. In the first part of this paper, the distance transformation using mathematical morphology is developed. In the second part, several approximations of the Euclidean distance are discussed. In the third part, the decomposition of the Euclidean distance structuring element is presented. The decomposition technique employs a set of 3 by 3 gray scale mor- phological erosions with suitable weighted structuring elements and combines the outputs using the minimum operator. Real- valued distance transformations are considered during the pro- cesses and the result is approximated to the closest integer in the final output image.