V.F. Leavers. Shape Detection in Computer Vision Using the Hough Transform. Springer-Verlag, 1992. Home/Search Document Not in Database Summary Related Articles Check |
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Learning a Navigation Task in Changing Environments by.. - Grossmann, Poli (Correct)
....hardly any distance readings from the front sonars are correct. In further investigations, we developed a localisation method [8] that works reliably in our setup. The approach consists of three steps. First, we compute a two dimensional feature space by applying a straight line Hough transform [14] to the sonar readings. Second, we perform template matching in the feature space by using the world map as reference pattern. Third, we use the correlation counts obtained in the previous step to update a position probability grid. This method, which is to our knowledge the only sonar based ....
V. F. Leavers. Shape Detection in Computer Vision Using the Hough Transform. Springer, London, UK, 1992.
Efficient 3D Vertex Detection in Range Images Acquired with.. - Katsoulas, Bergen (Correct)
....and accumulating feature parameters from sampled points. While this reduces the computational complexity of the accumulation to some extent, the complexity of the peak detection and the memory requirements remain unchanged. Leavers developed the dynamic generalized Hough transform (DGHT) cf. [8]) a technique which allows for the use of one dimensional accumulators if a coarse segmentation of the objects can be obtained and if the features under detection can be suitably parameterized. This technique, which belongs to the group of PHTs, reduces the memory requirements from R n to nR, ....
V. F. Leavers. Shape Detection in Computer Vision Using the Hough Transform. Springer-Verlag, London, 1992.
Using an Extended Hough Transform Combined with a Kalman.. - Behrens, Rohr, Stiehl (Correct)
....derivations for an adaptive sample size, and a novel input weighting scheme. 2. 1 Object Parameterisations for Ellipses and Straight Elliptical Cylinders To detect ellipses in 2D slices of elliptical generalized cylinders, we apply an ellipse parameterisation proposed for the Hough transform in [13]. Given five coplanar points, this approach determines the unique ellipse (if there is any) that passes through them. Let # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ....
V. F. Leavers. Shape Detection in Computer Vision Using the Hough Transform. SpringerVerlag, London, 1992, p. 151.
Automatic determination of the center of rotation of.. - van der Glas, Vos.. (Correct)
....in binary 2D images [10] In the next section the method is explained. It is tested on some artificial images and used to determine the center of the humeral head in 3D images generated by a CT and a MRI scanner. Section 3 shows the results of these experiments. 2 Methods The Hough transform [11] is a well accepted method used for shape detection in binary images. It uses segmented images to determine the parameters of pre defined shapes. As the joint surfaces may be obtained by a simple threshold it is convenient to develop a method related to the Hough transform. The novelty in our ....
V.F. Leavers. Shape detection in computer vision using the Hough transform. Springer Verlag, 1992.
Performance of the Hough transform on a distributed.. - Underhill.. (Correct)
....of granularity (ratio of computation to communication) on the speedup. The Hough transform is used to detect geometric patterns in images and is known to be very compute intensive. There has been much work carried out on the Hough transform in the last two decades for single processor machines [3]. The nature of the Hough transform algorithm reveals that each feature point in the image can be treated independently. Thus, it is possible to process each of these points concurrently. This inherent parallelism has attracted much attention. Implementations of the transform using various ....
V. Leavers, Shape Detection in Computer Vision using the Hough Transform, Springer, London, 1992.
Numerically Stable Direct Least Squares Fitting Of Ellipses - Halir, Flusser (1998) (1 citation) (Correct)
....applications of computer vision like 3 D vision and object recognition, medical imaging, industrial inspections, etc. Regarding the importance of ellipses, many different methods have been proposed for their detection and fitting. The approaches exploit various ideas (for example Hough transform [Leave92, Yuen89, Yin92, Wu93], RANSAC [Rosin93, Werma95] Kalman filtering [Porri90, Rosin95] fuzzy clustering [Dave92, Gath95] or least squares approach [Haral93, Books79, Taubi91, Samps92, Gande94] but in principle they can be divided into two main groups: voting clustering and optimization methods. The methods ....
Leavers, V. F.: Shape Detection in Computer Vision Using the Hough Transform. Springer-Verlag, 1992.
Robust Mobile Robot Localisation from Sparse and Noisy.. - Großmann, Poli (1999) (Correct)
....localisation algorithm that avoids the problem that a single wall is perceived only as set of non contiguous segments has been reported in the literature. 3 Detecting walls and corners with the Hough transform The Hough Transform (HT) is well known in computer vision as a shape detection method [2, 9]. In general, its purpose is to detect parametric curves in sets of primitive feature points. It has the advantage of being relatively una ected by gaps in curves and by noise. It would appear that the Hough transform can also be used to detect straight line segments in sonar data. 3.1 The Hough ....
V. F. Leavers. Shape Detection in Computer Vision Using the Hough Transform. Springer, London, UK, 1992.
Stable Segmentation of 2D Curves - Fitzgibbon (1997) (Correct)
....presenting some possible extensions. 3.2 Previous Methods and their Limitations The literature on ellipse fitting divides into two general techniques: clustering and leastsquares fitting. Clustering methods are based on mapping sets of points to the parameter space, such as the Hough transform [65, 133] and RANSAC [14] or accumulation methods [103] These Hough like techniques have some great advantages, notably high robustness to occlusion and no requirement for pre segmentation, but they suffer from the great shortcomings of high computational complexity and non uniqueness of solutions, which ....
V.F. Leavers. Shape Detection in Computer Vision Using the Hough Transform. Springer-Verlag, 1992.
Trace Extraction From Oblique Ionograms. - Applied Machine Vision (Correct)
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V.F. Leavers. Shape Detection in Computer Vision Using the Hough Transform. Springer-Verlag, 1992.
Automated Mode Separation In Oblique Ionograms - Roughan Cooperative Research (1996) (Correct)
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V.F. Leavers, Shape Detection in Computer Vision using the Hough Transform. Springer Verlag, 1992.
Robust Mobile Robot Localisation from - Sparse And Noisy (Correct)
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V. F. Leavers. Shape Detection in Computer Vision Using the Hough Transform. Springer, London, UK, 1992.
X-ray Image Analysis - Abeynayake (2001) (Correct)
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F.Leavers V. Shape Detection in Computer Vision Using the Hough Transform. Springer-Verlag, 1992.
Trace Extraction From Oblique Ionograms - Roughan And Percival (1996) (Correct)
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V.F. Leavers, Shape Detection in Computer Vision using the Hough Transform. Springer Verlag, 1992.
Automated Mode Separation in Oblique Ionograms - Roughan (1996) (Correct)
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V.F. Leavers, Shape Detection in Computer Vision using the Hough Transform. Springer Verlag, 1992.
Trace Extraction from Oblique Ionograms - Roughan (2003) (Correct)
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V.F. Leavers. Shape Detection in Computer Vision Using the Hough Transform. Springer-Verlag, 1992.
Part-based Grouping and Recognition: A Model-Guided Approach - Pilu (1996) (1 citation) (Correct)
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V.F. Leavers. Shape Detection in Computer Vision Using the Hough Transform. Springer-Verlag, 1992.
Visual Curb Localization for Autonomous Navigation - Turchetto, Manduchi (Correct)
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V.F. Leavers, Shape Detection in Computer Vision Using the Hough Transform, Springer--Verlag, 1992.
A short introduction to the Radon and Hough transforms and .. - van Ginkel, van Vliet (2004) (Correct)
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V.F. Leavers. Shape Detection in Computer Vision Using the Hough Transform. Springer-Verlag, London, 1992.
Direct Least Squares Fitting of Ellipses - Andrew Fitzgibbon Maurizio (1996) (37 citations) (Correct)
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V. Leavers. Shape Detection in Computer Vision Using the Hough Transform. Springer-Verlag, 1992.
Direct least Square Fitting of Ellipses - Andrew Fitzgibbon Maurizio (1996) (37 citations) (Correct)
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V.F. Leavers. Shape Detection in Computer Vision Using the Hough Transform. Springer-Verlag, 1992.
Robust Mobile Robot Localisation from Sparse and Noisy.. - Großmann, Poli (1999) (Correct)
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V. F. Leavers. Shape Detection in Computer Vision Using the Hough Transform. Springer, London, UK, 1992.
Continual Learning for Mobile Robots - Großmann (2001) (Correct)
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V. F. Leavers. Shape Detection in Computer Vision Using the Hough Transform. Springer, London, UK, 1992.
The Hough Transform As A Tool For Image - Analysis Josep Llados (Correct)
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V.F. Leavers. Shape Detection in Computer Vision Using the Hough Transform. Springer-Verlag, 1992.
Feature-Based Detection of Landmines in Infrared Images - Messelink, Schutte.. (2002) (Correct)
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V. Leavers. Shape Detection in Computer Vision Using the Hough Transform. Springer-Verlag, 1992.
Determination of Position and Radius of Ball Joints - Marjolein Van Der (2002) (Correct)
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V. Leavers, Shape detection in computer vision using the Hough transform, Springer Verlag, 1992.
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