Vol. 10 (2001): Abstracts of Papers
Haider Md.A., Kaneko T.:
Reconstruction of 3D human hair shape from video captured images and CT data.
MGV vol. 10, no. 1, 2001, pp. 3-14.
We propose a three-dimensional (3D) reconstruction method of human hair-shape from rotating head multiple video captured images and CT data. It is well known that no hair is present on the polygonal skin surface of the human head (3D-head) reconstructed from CT or MRI data. Our task is to reconstruct and add the hair-shape on the 3D-head to create a realistic human head model for simulating post-surgical facial expressions. Using a sculpturing technique based upon rotating head images we propose a method of reconstructing the hair-shape as well as the concave and semi-occluded parts in the skin-hair junction regions. We have utilized binarized voxel data of the 3D-head (solid-head) in this regard. The sculpturing object in our definition is the solid-head surrounded by assumed thick hair-voxels. We sculpture the surrounding hair-voxels according to the extracted hair-region from the video captured images while keeping the internal solid-head intact. We reconstruct the concave and semi-occluded regions by digging up to the visible skin surface of the solid-head in/near the hair region. We define complete-model as the 3D polygonal surface obtained from solid-head including the residue sculptured hair-voxels on it. Experimentally we have shown that our method yields hair shape to be used in practice.
Key words: 3D reconstruction, 3D head modeling, 3D hair modeling, visualization.
Tefera D.A., Harada K.:
A complement to the 8 point algorithm in matching uncalibrated image sequences of a scene.
MGV vol. 10, no. 1, 2001, pp. 15-27.
This paper presents an algorithm which generates an initial set of matching corner points between two uncalibrated images of the same scene. Matching different images of a single scene remains one of the bottlenecks in computer vision. The major part of matching algorithms is to recover the epipolar geometry, which heavily depends on the accuracy of the set of eight corresponding points that are used to calculate the fundamental matrix between the sets of images under consideration. Thus, an algorithm to locate a reliable initial guess for matching corner points is proposed. The algorithm has been tested and shown reliable with different types of images indicating its ability to localize reliable sets of matching corner points. With the help of non-maximum response suppression technique our approach yields better results than other methods.
Key words: matching, correspondence problem, epipolar geometry, corners, bubble sorting.
El-henawy I., Fouda Y.M., Enab Y.M.:
A neurocomputing approach to the correspondence problem in stereo vision based upon an unsupervised neural network.
MGV vol. 10, no. 1, 2001, pp. 29-46.
The stereo matching problem is one of the most widely studied problems in stereo vision. In this paper we introduce a neurocomputing approach to the local stereo matching problem using edge segments as features with several attributes. Most classical local stereo matching techniques use features representing objects in both images and compute the minimum values of attribute differences. Pajares et al. had verified that the differences in attributes, for the true matches, cluster in a cloud around a center. We use the self-organizing neural network to get the best cluster center. Based on the similarity constraint, we compute the minimum Mahalanobis distances between the differences of the attributes for a new pair of features and the cluster center to classify this new pair as true or false match. Experimental results with two real pairs of images are shown.
Key words: computer vision, stereo vision, matching, unsupervised neural network.
Automatic human face recognition using modular neural networks.
MGV vol. 10, no. 1, 2001, pp. 47-73.
In this paper, a fast biometric system for personal identification through face recognition is introduced. In the detection phase, a fast algorithm for face detection is combined with cooperative modular neural networks (MNNs) to enhance the performance of the detection process. A simple design for cooperative modular neural networks is described to solve this problem by dividing the data into three groups. Furthermore, a new faster face detection approach is presented through image decomposition into many sub-images and applying cross correlation in frequency domain between each sub-image and the weights of the hidden layer. For the recognition phase, a new concept for rotation invariant based on Fourier descriptors and neural networks is presented. Although the magnitude of the Fourier descriptors is translation invariant, there is no need for scaling or translation invariance. This is because the face sub-image (20x20 pixels) is segmented from the whole image during the detection process. The feature extraction algorithm based on Fourier descriptors is modified to reduce the number of neurons in the hidden layer. The second stage extracts wavelet coefficients of the resulted Fourier descriptors before application to neural network. The final vector is fed to a neural net for face classification. Moreover, a modified hierarchy soft decision tree of neural networks is introduced for face recognition. Compared with previous results, the proposed algorithm shows good performance on recognizing human faces with glass, beard, rotation, scaling, occlusion, noise, or change in illumination. Also, the response time is reduced.
Key words: face detection, modular neural networks, image decomposition, local image normalization, face recognition, rotation invariance.
Accuracy prediction in a 3D active triangulation scanner.
MGV vol. 10, no. 1, 2001, pp. 75-87.
An active triangulation 3D scanner was developed at the Budapest University of Technology and Economics, Department of Automation. In the first part of this paper the configuration of the 3D scanner system will be presented. Then the edge tracking part of model extraction algorithm will be described, especially focusing on the handling of noise. Accuracy of the generated CAD model depends on configuration parameters and the noise of the frame buffer image can be taken into consideration. The last part of the paper presents a workflow for the adequate handling of accuracy, as a function of a certain noise model. Since the development is focused on the accuracy of methods instead of expensive hardware elements, it is essential to know the theoretical capabilities of the system. The focus of the paper is finding the initial point of edge tracking, the accuracy of angle calculation and the accuracy of line tracking supposing a noise model. Finally some experiment results are demonstrated.
Key words: 3D scanner, edge tracking, CAD object model, noise model.
Reinoso O., Sebastián J.M., Aracil R., Torres F.:
Morphological operations with subpixel resolution on digital images.
MGV vol. 10, no. 1, 2001, pp. 89-102.
In many defect inspection systems computer vision pattern matching techniques are applied. These techniques require the use of different morphological operations. In many situations, pattern images generated by classical morphological operations do not allow to detect defects in images. Small defects of pixel size can also be left unnoticed when using such pattern images. The purpose of this paper is to combine classical morphological operations with a linear interpolation process on digital images to generate these pattern images. It is possible to employ structuring elements of any size to carry out morphological operations on continuous signals. However, on digital images or discrete signals, the size of the structuring element should be greater than pixel size. The approach described in this paper applies classical morphological operations on reconstructed images at subpixel level to generate pattern images. In such circumstances, we can compare this procedure with the effect produced by the use of structuring elements smaller than pixel size.
Key words: morphological operations, pattern matching, sub-pixel accuracy, linear interpolation.
Wang J., Lin Z., Zhu J.:
A novel recognition method for color objects under different illuminations.
MGV vol. 10, no. 1, 2001, pp. 103-112.
Color images depend on the scene illumination, but these image colors are not stable features for object recognition. We develop an algorithm that transforms color into its normal form such that it is invariant to different illuminations. Since the normalization process is to make color image compact, colors distorted in different ways from the same object due to illumination change will all be compacted to their most compact form and become similar. After compaction process, the histograms for the same objects under different illuminations are very similar. The recognition can be performed by simple matching method. A set of experiments on complex scenes under various illumination conditions demonstrate superiority of our proposed method in term of recognition rate over other reported techniques for color normalization.
Key words: affine transform, color image compaction, covariance, histogram, invariant image matching.
Kim S.-H., Park R.-H.:
Fast range image registration using distance sampling.
MGV vol. 10, no. 2, 2000, pp. 115-131.
This paper proposes a fast range image registration algorithm, in which control points are sampled on the basis of distance from the geometric origin of an object. The sampled point is assumed to be in the same region if the quantization error in the three-dimensional space is less than a threshold. For range image registration, finding matching points only in the same region reduces the computation time greatly. Experiments with various synthetic and real images show that the accuracy of registration parameters is improved with a low computational load.
Key words: range image, registration, iterative closest point (ICP) algorithm, quaternion, rotation, translation, sampling and grouping by the distance.
Adhami L., Abdel-Malek K., McGowan D., Sameh A.:
A partial surface/volume match for high accuracy object localization.
MGV vol. 10, no. 2, 2000, pp. 133-154.
A new surface/volume rigid registration method is proposed that allows fast and robust convergence. In this work, rigid bodies are modeled using a matrix of voxels and its associated compressed voxel representation (V-rep). The two models are fused to obtain an indication of the quality of the match. Optimization techniques using gradient descent and/or genetics algorithms are implemented to select the appropriate transformations, where the search space is established. A sequence of translations and rotations are applied to one of the models until an appropriate match is reached through this space search. Unique data structures are introduced to efficiently store the data. The method and an experimental computer code are demonstrated in the paper.
Key words: surface matching, registration, bone surface identification.
Xu Z., Toncich D., Wu H.:
Vision-based high accuracy work-piece inspection from profiles.
MGV vol. 10, no. 2, 2000, pp. 155-174.
The objective of the research documented herein was to investigate high-accuracy identification and measurement of a work-piece through edge detection, and to derive its three-dimensional properties from a profile of the work-piece image. A number of techniques for providing the transformation of the image are also described. The helix, helicoid and range of geometric entities have been selected to demonstrate the methodology and to highlight various aspects of the proposed techniques.
Key words: vision systems, measurement of geometric properties, edge detection, image analysis, three dimensional shape.
Zeng P.F., Hirata T.:
Interpolatory edge detection.
MGV vol. 10, no. 2, 2000, pp. 175-184.
Conventional edge operators cannot detect fine edges or edges in low-resolution images in a satisfactory way. In this paper, an interpolatory edge operator is proposed to deal with fine edge detection as a supplement. Fast image expansion is implemented by means of B-spline interpolation. Edges are determined by seeking pixels with a local maximum of first derivative modulus ( modulus maximum). The first derivatives can be calculated quickly by translation and subtraction along x and y directions of images interpolated by B-splines. Experimental results imply that the proposed interpolatory edge operator can satisfactorily solve the fine edge detection problem in cases when conventional edge operators fail to produce a clear output. Satisfactory results can be obtained when images are interpolated with the expansion rate of three.
Key words: B-spline, image interpolation, edge detection.
Computer graphics analysis: a method for arbitrary image shape description.
MGV vol. 10, no. 2, 2000, pp. 185-194.
A concept of a new set of features suitable for describing arbitrary shapes after their thinning is presented. The features are the minimal eigenvalues of Toeplitz matrices formed from rational functions, in which the coordinates of the characteristic pixels of the shape to be described are used as coefficients, the x coordinates in the numerator polynomial, and the y coordinates in the denominator polynomial. Each rational function has a form which makes it a general measure of image description and its features extraction. The method is introduced and applied for the first time.
Key words: image recognition, image shape description, computer graphics, feature extraction, Toeplitz-matrices applications.
Linear features detection in SAR images.
MGV vol. 10, no. 2, 2000, pp. 195-205.
The constant false alarm rate "ratio" edge detector has proved suitable for synthetic aperture radar (SAR) images. In this paper, we introduce another ratio detector that uses a half-gaussian weight function for better localization of linear features, and multiscale functions for finer detection. A recursive implementation is proposed in order to reduce the computing time. Tests on 3-view SAR ERS-1 images as well as on a speckled simulated image are given.
Key words: linear features detection, geometric filter, statistics, SAR images.
Konevsky O. L.:
Smoothing of binary raster images using mathematical morphology.
MGV vol. 10, no. 2, 2000, pp. 207-220.
A new method for preparation of binary raster images for curve detection and subsequent processing is described in this paper. The proposed technique allows to smooth binary raster images using basic operators of mathematical morphology in order to eliminate defects and reduce noise while preserving the topology of the object. The processing parameters are adjusted automatically to the particular image depending on its features.
Key words: mathematical morphology, smoothing, raster image.
Hassanien A.E., Henawy I.E., Own H.:
Multiresolution image denosing based on wavelet transform.
MGV vol. 10, no. 2, 2000, pp. 221-230.
Wavelet-based image denoising is a very attractive tool for analysis and synthesis of functions. It enables us to divide a complicated function into several simpler ones and study them individually. In this paper, we present a new image-denoising algorithm based on multiresolution local contrast entropy of wavelet coefficients. Depending on the probability distribution of the noise in the wavelet coefficients, a new adaptive threshold estimation algorithm is introduced. This threshold enables the proposed algorithm to adapt to unknown smoothness of denoised images. The experiments performed confirm that the proposed algorithm is capable of achieving good results for additive white gaussian noise.
Key words: multiresolution, local contrast entropy, denoising, wavelet transform, thresholding, image processing.
The computer analysis of images in application to the measurement of the vehicles movement parameteres.
MGV vol. 10, no. 2, 2000, p. 231.
Special Issue on Stereogrammetry and Related Topics.
Special Issue Editor: Leszek Chmielewski.
Vincent E., Laganière R.:
Matching feature points in stereo pairs: a comparative study of some matching strategies.
MGV vol. 10, no. 3, 2001, pp. 237-259.
Several algorithms are proposed in the literature to solve the difficult problem of feature point correspondence between image pairs. In order to obtain good quality results, they make use of different approaches and constraints to improve the quality of the matching set. A matching strategy is considered useful if it is able to filter out many of the mismatches found in an input matching set while keeping in most of the good matches present. In this paper, we present a survey of different matching strategies. We propose an empirical evaluation of their performance. The validation process used here determines the number of good matches and the proportion of good matches in a given match set for the different parameter values of a matching constraint.
Key words: feature point correspondence, stereo matching, interest point detection, corners.
Jan J., Janová D.:
Complex approach to surface reconstruction of microscopic samples from bimodal image stereo data.
MGV vol. 10, no. 3, 2001, pp. 261-288.
The paper describes a set of approaches and methods enabling robust and relatively precise stereo-analysis-based surface reconstruction in scanning electron microscopy (SEM). The paper primarily deals with the disparity analysis problem, namely with selection of a suitable similarity criterion to be used for finding image correspondences. The search-and-match method (as opposed to feature-based analysis) is shown as probably the only practical solution in the given environment of SEM when no prior constraints on the surface type are allowed. Extensive comparison of some common and newly suggested similarity criteria lead to the conclusion that the designed angle criterion is the only one acceptable so far with respect to the error rate. Use of the criterion has been shown equivalent to applying a non-linear two-dimensional matched filter, which enables efficient frequency domain implementation in the form of a linear matched filter modification. An important improvement in reliability of the computed disparities has been achieved by using both available imaging modalities (back-scattered electrons - BEI and secondary electrons - SEI), thus providing vector image data. Expressing the criterion for the vector case in terms of both individual scalar cases cuts computational requirements by half, besides allowing for an additional reliability criterion - comparison of three different, though partly, dependent criteria. Secondly, the comprehensive approach includes also solutions of problems which may seem marginal but are important for the practical success of the analysis. Recent improvements, solving some of such specific problems of SEM stereo analysis, are discussed as well. The paper summarises the present state of the method's development over the past few years partial descriptions of which can be found scattered in previous publications devoted to individual specific problems.
Key words: surface reconstruction, scanning electron microscopy, bimodal images, image analysis, stereo, disparity analysis, similarity critera.
Novel feature-based stereo matching method that employs tensor representation of local pixels neighborhoods in images.
MGV vol. 10, no. 3, 2001, pp. 289-316.
Stereo matching techniques have evolved substantially throughout recent years. However, the problem of unambiguous stereo points matching, especially in presence of object occlusions, as well as images noise and distortions, remains still open. In this paper, a novel feature-based stereo matching method, based on tensor representation of local structures in digital images, has been described. Application of a structural tensor enables more reliable matching of locally coherent structures, representing averaged dominant gradients in local neighborhoods rather than sparse points. The presented work has been completed with many experiments that confirmed its usefulness, especially in a case of real stereo images.
Key words: stereo vision, stereo matching, depth recovery, structural tensor.
Rziza M., Aboutajdine D.:
New stereo vision matching algorithm based on constrained dynamic programming and higher order statistics criteria.
MGV vol. 10, no. 3, 2001, pp. 317-331.
We present a new efficient stereo algorithm addressing robust disparity estimation in the presence of noise. We propose here a new constrained dynamic programming algorithm based on Higher Order Statistics (HOS) criteria for matching noisy images. Experiments with both synthetic and noisy real images have validated our method and have clearly shown the improvement over the existing ones. The obtained dense disparity map is more reliable when compared to the similar Second-Order Statistics (SOS) based constrained dynamic programming and HOS-based correlation methods.
Key words: rectification, disparity, matching, correlation, dynamic programming, constrained dynamic programming, higher order statistics, cumulant.
Self-matching of stereoscopic images without camera calibration.
MGV vol. 10, no. 3, 2001, pp. 333-351.
In computer vision applications where the calibration object is not available, it is useful to use an uncalibrated stereoscopic head. Even in this case, to calculate the three-dimensional structure of the viewed scene, the stereo matching is considered as the key step in stereo vision analysis. This paper presents a contribution to resolve this problem when an uncalibrated stereo rig is involved in a visual task. We propose an algorithm for self-matching of stereoscopic images of indoor scenes. Based on projective geometry, the principal idea of the method is to estimate the epipole position assuming a set of matched 2D surfaces. A voting approach is used to select the correct matches which produce the same solution. In practice, as the stereo images are noisy, we propose a mathematical analysis of the uncertainty measure. We assume that the vertices are noisy, and we propagate the effect of this noise in the different stages of the proposed algorithm. The new version of the algorithm allows to calculate the region where the epipole point appertains, called the "epipolar region". The stereo matching algorithm has been tested on both synthetic and real images, and the number of lines matched demonstrates the robustness of the geometric method.
Key words: stereovision, matching, projective geometry, cross ratio, 2D surface, noise, epipole.
Williams J.G., Blake E.H., Ruther H.:
Extraction of data from low quality photographs to aid the construction of virtual reality models of archaeological sites.
MGV vol. 10, no. 3, 2001, pp. 353-368.
A tool has been constructed to use information extracted from photographs captured using uncalibrated cameras to fill occlusions which occur in three-dimensional models of photogrammetrically captured sites. Capturing the geometry of archaeological sites by photogrammetric means is relatively expensive and, because of the typical layouts of such sites, usually results in a degree of occlusion.
The essential philosophy underlying the tool is to segment each occlusion into surfaces which may be approximated using curves, and then use the known geometry in the region of the occlusion to calculate the most probable locations of the junctions of such surface segments. Texture of the surface segments is then applied to the three-dimensional model.
The tool has been applied to occlusions of various configurations that are expected to be typical for archaeological sites, and has been found to deal well with such features and to provide accurate patches from typical data sets. It is also shown that the three-dimensional geometric model is clearly improved by the filling-in of the occlusion.
Key words: texture extraction, geometry calculation, occlusion, photogrammetry.
Peer P., Solina F.:
Capturing mosaic-based panoramic depth images with a single standard camera.
MGV vol. 10, no. 3, 2001, pp. 369-397.
In this paper we present a panoramic depth imaging system. The system is mosaic-based which means that we use a single rotating camera and assemble the captured images in a mosaic. Due to a setoff of the camera's optical center from the rotational center of the system we are able to capture the motion parallax effect, which enables the stereo reconstruction. The camera is rotating on a circular path with the step defined by an angle equivalent to a single column of the captured image. The equation for depth estimation can be easily extracted from the system geometry. To find the corresponding points on a stereo pair of panoramic images, the epipolar geometry needs to be determined. It can be shown that the epipolar geometry is very simple if we are doing the reconstruction based on a symmetric pair of stereo panoramic images. We get a symmetric pair of stereo panoramic images when we take symmetric columns on the left and on the right side from the captured image center column. Epipolar lines of the symmetrical pair of panoramic images are image rows. We focuse mainly on the system analysis. The system performs well in the reconstruction of small indoor spaces.
Key words: stereo vision, reconstruction, panoramic image, depth image, mosaicing, motion parallax effect.
Wei S.-K., Huang F., Klette R.:
Determination of geometric parameters for stereoscopic panorama cameras.
MGV vol. 10, no. 3, 2001, pp. 399-427.
This paper proposes an approach to solving the parameter determination problem for a stereoscopic panorama camera. The image acquisition parameters have to be calculated under given constraints defined by application requirements, the image acquisition model, and specifications of the targeted 3D scenes. Previous studies on stereoscopic panorama imaging have paid great attention on how a proposed imaging approach supports a chosen area of application. The image acquisition parameter determination problem has not yet been dealt with in these studies. The lack of guidance in selecting the image acquisition parameters affects the validity of results obtained for subsequent processes. Our approach towards parameter determination allows satisfying the common requirements of 3D scene visualization or reconstruction applications: a proper scene composition in the resultant images; an adequate sampling at a particular scene distance; and the desired stereo quality (i.e. depth levels) over diverse of scenes of interest. The paper details the models, constraints and criteria used for solving the parameter determination problem. Some practical examples are given in order to demonstrate the use of the formulas derived. The error analysis of our determination approach is also carried out and elaborated in this paper. The study contributes to the design of stereoscopic panorama cameras as well as to manuals for on-site image acquisition. The results of our studies are also useful for camera calibration, or pose estimation in stereoscopic panoramic imaging.
Key words: panorama camera, image acquisition, line camera, stereoscopic panorama.
Cheng B., Li X., Zheng N., Quan W.:
3D plenoptic representation of a linear scene.
MGV vol. 10, no. 4, 2001, pp. 431-446.
This paper presents a novel 3D plenoptic function. We constrain camera motion to a line, and create a linear mosaic using a manifold mosaic. The plenoptic function is represented with three parameters: camera position along the axis, the angle between the ray and the centric axis, and the rotation angle in the vertical plane. Novel views are rendered by combining the appropriate captured rays in an efficient manner at the rendering time. Like panoramas, our method does not require recovery of geometric and photometric scene models. Moreover, it provides a much richer user experience by allowing the user to move freely in a linear region and observe significant parallax and lighting changes. Compared with either Lightfield or Lumigraph, it has a much smaller file size because a 3D only plenoptic function is constructed. Finally, an experiment with a synthetic environment is given to demonstrate its efficiency in capturing, construction and rendering of a linear scene.
Key words: plenoptic function, virtual environments, image-based rendering, linear mosaic
Kasinski A.J., Hamdy A.M.:
Segmentation based on homomorphic filtering and improved seeded region growing for mobile robots tracking in image sequences.
MGV vol. 10, no. 4, 2001, pp. 447-466.
In this paper, we present a method for extracting and tracking of mobile robots in a sequence of noisy frames, assuming a complex background composed of textured floor, illuminated unevenly. A homomorphic filter is used, as a preprocessor, to enhance the acquired frames by eliminating the illumination component and emphasizing the reflectance component of the image function. To speed up preprocessing of each frame, filtering is only applied to the pixels belonging to the regions of interest (ROI). In all the tested cases, homomorphic-filtering led to better results than those obtained without preprocessing.
The segmentation process has been based on seeded region growing procedure for reconstructing the shape of the mobile robot. We proposed automatic seed points selection in the binarized difference image, and use of an adaptive threshold. This use eliminates or at least considerably reduces false negative detections, and reduces sensitivity of aggregation results to the selected seed points as compared to the classical seeded region growing procedure. Additionally, by imposing a condition of strong connectivity between a seed point and its neighborhood, aggregation of undesired pixels efficiently eliminates false positive detections. Implementation of segmentation and tracking can be run in real time. High tracking accuracy has been obtained through out all the frames in a test sequence.
Key words: adaptive threshold, homomorphic filtering, motion segmentation, seeded region growing, visual tracking.
Kim H.S., Yang Y.K.:
An automatic classification technique for indexing of soccer highlights using neural networks.
MGV vol. 10, no. 4, 2001, pp. 467-487.
A method for automatic classification of offensive play patterns in soccer games has been developed using the neural networks technique. Back-propagation (BP) neural network techniques have been applied to obtain data that define the positions of both a player and the ball on the ground. The offensive play patterns that have been formulated from the group formations enable automatic indexing of the highlights of soccer games. Excepts from actual soccer games, including some from the 1998 French World Cup, yielded 297 video clips which were categorized into the following five types of patterns: Left-Running are 60, Right-Running 74, Center-Running 72, Corner-Kick 39 and Free-Kick 52. Examination of the results shows the following rates of satisfactory pattern recognition: Left-Running comes to 91.7%, Right-Running 100%, Center-Running 87.5%, Corner-Kick 97.4% and Free-Kick 75%.
Key words: Soccer game, offensive play patterns, neural network, BP algorithm, group formation.
Otero J., Otero A., Sànchez L.:
Mode based hierarchical optical flow estimation.
MGV vol. 10, no. 4, 2001, pp. 489-501.
In this paper, a robust estimation of the optical flow field that preserves the boundaries of the movement is shown. Arising from the techniques based on the Optical Flow Constraint (OFC), an estimation that takes several measures around a given pixel, discarding the erroneous ones, has been developed. This is done through performing a bidimensional clustering of the velocities obtained from the intersection of pairs of OFCs. In this way, the clustering is conducted in the velocity space and not in the (slope, intercept) parameter space of the OFCs. Finally, a hierarchical implementation that has a lesser error when large displacements are present in the image is shown.
Key words: computer vision, motion analysis, optical flow, robust estimation.
Jun Wei H., Lei G.:
An algorithm for automatic detection of runways in aerial images.
MGV vol. 10, no. 4, 2001, pp. 503-518.
This paper presents an automatic algorithm to detect runways of the military airport in aerial images. Firstly, we design a model of runway based on its features. Then, we find the runway in a hypothesis and test paradigm. Hypotheses are formed by looking for instances of long rectangular shapes. Runway intensity and intensity contrast between the runway and background are used to verify our hypotheses. Finally, the hypothesis that is supported by verification is believed to be the runway. Many experiments demonstrate that this algorithm can find runways of a military airport effectively.
Key words: runway, edge, edge tracking, straight line, anti-parallel.
Grabska E., Slusarczyk G., Niewiadomska A.:
Hierarchical graph grammars in graphic prints design and generation.
MGV vol. 10, no. 4, 2001, pp. 519-536.
The paper deals with graphic prints in Escher's style and hierarchical graphs. Escher prints are based on regular plane divisions, while hierarchical graphs represent plane division structures. The paper is illustrated by graphic prints generated by the system ESCHER_GRAPHICS.
Key words: graph, graphical model, graph grammar, graphic print.
The metamorphosis of 3D binary objects using morphological interpolation.
MGV vol. 10, no. 4, 2001, pp. 537-550.
This paper presents a new method of metamorphosis of three-dimensional objects by means of an interpolation method based on mathematical morphology supported by an affine transform. The metamorphosis is a process of smooth transformation of one object into another, the result of which is stored in a sequence of 3D images. The proposed method is automatic - the only data necessary consists of: two input 3D binary objects (the initial one and the final one) and an additional parameter - either the number of frames in the final sequence or the highest value of the dissimilarity measure. The method consists in performing successive computations of morphological median objects. The proposed interpolation scheme is a new application of morphological interpolation to 3D image metamorphosis. Also, it combines 3D morphology with affine object matching. The proposed interpolation sequence algorithm is a new one and allows us to produce the interpolation sequence by considering dissimilarity measures between the consecutive frames. The method can be applied to animation in computer graphics and visualization of three-dimensional data.
Key words: 3D objects interpolation, volume morphing, mathematical morphology, morphological interpolation.
Contents of volume 10, 2001