Results 131 to 140 of about 1,992 (180)

SR-LMamba: A lane detection model for complex scenes integrating curvelet transform with Mamba architecture. [PDF]

PLoS One
Chen M, Jia Q, Yang J, Liu S.
europepmc   +1 more source

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A fast Hough transform for segment detection

IEEE Transactions on Image Processing, 1995
The authors describe a new algorithm for the fast Hough transform (FHT) that satisfactorily solves the problems other fast algorithms propose in the literature-erroneous solutions, point redundance, scaling, and detection of straight lines of different sizes-and needs less storage space.
Nicolas Guil, J Villalba, E L Zapata
exaly   +3 more sources

A fast digital Radon transform—An efficient means for evaluating the Hough transform

Pattern Recognition, 1995
A fast digital Radon transform based on recursively defined digital straight lines is described, which has the sequential complexity of N^2 log N additions for an N x N image. This transform can be used to evaluate the Hough transform to detect straight lines in a digital image.
W. A. Götz, H. J. Druckmüller
exaly   +2 more sources

Connectivity oriented fast Hough transform for tool wear monitoring

Pattern Recognition, 2004
Abstract Tool wear monitoring can be achieved by analyzing the texture of machined surfaces. In this paper, we present the new connectivity oriented fast Hough transform , which easily detects all line segments in binary edge images of textures of machined surfaces.
Ashraf A Kassim, M A Mannan
exaly   +2 more sources

Fast Hough transform algorithm for radar detection

2010 The 2nd International Conference on Industrial Mechatronics and Automation, 2010
In this paper, a fast algorithm for radar detection based on line Hough transform is presented. Unlike the traditional method, the idea of our proposed is that the point of data space should be mapped into the Hough parameter space of slope and intercept, where the relative position of the points in the data space is preserved.
Zeng Jiankui, null Xiang Lijuan
exaly   +2 more sources

Fast Dual-Point Hough Transform for medical object recognition

2010 IEEE 23rd International Symposium on Computer-Based Medical Systems (CBMS), 2010
In this paper we introduce a new object recognition method for detecting objects of arbitrary shapes based on a combination of the Fast Hough Transform (FHT) and the Dual-Point Generalized Hough Transform (DPGHT). We validate the proposed approach on medical images (cryosection, US, MRI) and describe its basic features. The proposed algorithm is robust,
Alena Bakulina, Dzmitry Hlindzich, Reinhard Maenner   +2 more
exaly   +2 more sources

Fast generalized Hough transform

Pattern Recognition Letters, 1990
Abstract A fast algorithm for the generalized Hough transform (GHT) based on the use of a hierarchical processing scheme and the inverse generalized Hough operation is proposed. By reducing the size of the image portion which need be processed in the proposed fast GHT, not only the computation time but also the number of processing elements for ...
Sheng-Ching Jeng, Wen-Hsiang Tsai
openaire   +1 more source

Analysis of Properties of Dyadic Patterns for the Fast Hough Transform

Problems of Information Transmission, 2021
We obtain an estimate for the maximum deviation from a geometric straight line to a discrete (dyadic) pattern approximating this line which is used for computing the fast Hough transform (discrete Radon transform) for a square image with side $$n=2^p$$ ,
Simon M. Karpenko, Egor I. Ershov
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Fast Hough transform: A hierarchical approach

Computer Vision, Graphics, and Image Processing, 1986
Abstract We have developed a fast algorithm for the Hough transform that can be incorporated into the solutions to many problems in computer vision such as line detection, plane detection, segmentation, and motion estimation. The fast Hough transform (FHT) algorithm assumes that image space features “vote” for sets of points lying on hyperplanes in ...
Hungwen Li, Mark A. Lavin, Ronald J. Le Master   +2 more
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Efficient Implementation of Fast Hough Transform Using CPCA Coprocessor

Programming and Computer Software, 2021
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F. A. Anikeev, G. O. Raiko, Elena Limonova, Mikhail A. Aliev, Dmitry P. Nikolaev   +4 more
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