scholarly journals An algorithm for extracting groove rail area based on improved Hough transform

2021 ◽  
Vol 336 ◽  
pp. 02025
Author(s):  
Zhongbin Fang ◽  
Xiaojie Huang ◽  
Kangquan Ye ◽  
Jing Ji ◽  
Qiantong Wu ◽  
...  
Keyword(s):  
Hough Transform ◽  
Line Length ◽  
Transform Method ◽  
Straight Line ◽  
Extraction Algorithm ◽  
Region Extraction ◽  
Actual Environment ◽  
Speed Up ◽  
Canny Edge ◽  
Edge Detection Method

In order to improve the accuracy and real-time performance of the automatic cleaning of groove rails in modern trams, this paper proposes a groove rail region extraction algorithm based on improved Hough transform. First, in order to speed up the detection and remove noise, the algorithm performs a series of pre-processing on the images collected by the camera, and then use the Canny edge detection method to extract the edge feature information of the groove rail. Finally, the algorithm is improved on the basis of the traditional Hough transform method according to the actual environment. The algorithm proposes three constraints from the straight line length, the slope of the straight line and the distance between the left and right edges, making the algorithm more feasible and accurate in extracting groove rail area. The extraction accuracy reached 97.9%, and the average extraction speed was 0.1903s, laying the foundation for the automatic cleaning of trough rails of modern trams.

Highway Lane Detection Based on a New Gray Method

2014 ◽  
Vol 1044-1045 ◽  
pp. 1553-1557
Author(s):  
Yan Zhou Peng ◽  
Hong Feng Gao
Keyword(s):  
Hough Transform ◽  
Color Image ◽  
Lane Detection ◽  
Gray Level ◽  
The Novel ◽  
Threshold Values ◽  
Transform Method ◽  
Illumination Changes ◽  
Canny Edge ◽  
Gray Level Image

a new gray method is provided in this paper for highway lane detection. Firstly, the novel gray method transform an RGB color image to a gray-level image based on a new gray vector. To deal with illumination changes, the new gray vector is updated on real-time.Secondly,the canny edge detector’s threshold values are decided adaptive.Lastly,Hough transform method realizes the detection of lanes. For different time in a day, experiments indicate that the proposed algorithm has good results.

scholarly journals Development of a Parcel-Level Land Boundary Extraction Algorithm for Aerial Imagery of Regularly Arranged Agricultural Areas

2021 ◽  
Vol 13 (6) ◽  
pp. 1167
Author(s):  
Rokgi Hong ◽  
Jinseok Park ◽  
Seongju Jang ◽  
Hyungjin Shin ◽  
Hakkwan Kim ◽  
...  
Keyword(s):  
Aerial Imagery ◽  
Mathematical Methods ◽  
Boundary Extraction ◽  
Distinctive Features ◽  
Straight Line ◽  
Extraction Algorithm ◽  
Canny Edge ◽  
Study Sites ◽  
Agricultural Areas

The boundary extraction of an object from remote sensing imagery has been an important issue in the field of research. The automation of farmland boundary extraction is particularly in demand for rapid updates of the digital farm maps in Korea. This study aimed to develop a boundary extraction algorithm by systematically reconstructing a series of computational and mathematical methods, including the Suzuki85 algorithm, Canny edge detection, and Hough transform. Since most irregular farmlands in Korea have been consolidated into large rectangular arrangements for agricultural productivity, the boundary between two adjacent land parcels was assumed to be a straight line. The developed algorithm was applied over six different study sites to evaluate its performance at the boundary level and sectional area level. The correctness, completeness, and quality of the extracted boundaries were approximately 80.7%, 79.7%, and 67.0%, at the boundary level, and 89.7%, 90.0%, and 81.6%, at the area-based level, respectively. These performances are comparable with the results of previous studies on similar subjects; thus, this algorithm can be used for land parcel boundary extraction. The developed algorithm tended to subdivide land parcels for distinctive features, such as greenhouse structures or isolated irregular land parcels within the land blocks. The developed algorithm is currently applicable only to regularly arranged land parcels, and further study coupled with a decision tree or artificial intelligence may allow for boundary extraction from irregularly shaped land parcels.

An Improved Hough Transform Algorithm Based on Pyramid Method

2014 ◽  
Vol 543-547 ◽  
pp. 1917-1921
Author(s):  
Long Ren ◽  
Jia Wen Liao ◽  
Jian Zhong Cao ◽  
Hua Wang ◽  
Xiao Dong Zhao ◽  
...  
Keyword(s):  
Computer Vision ◽  
Image Analysis ◽  
Standard Method ◽  
Hough Transform ◽  
Computational Time ◽  
Line Detection ◽  
Computation Complexity ◽  
Transform Method ◽  
Straight Line ◽  
Algorithm Base

Hough Transform[has become a common method in the usage of line detection because of its robustness. It is important in computer vision and image analysis. Usually, the standard Hough transform method (SHT) transform the points in image space into parameter space and vote for all the possible patterns passing through that point. But, there are two serious problems in the standard method of line detection. The first is the high computation complexity and the second is the large storage requirements .In order to solve the two problems, this paper raise a fast-Hough transform algorithm base on pyramid algorithm. First of all we need to desample the primitive binary image with n times; and execute the Hough transform in the nth level image to get the parameter of straight line in this image, which is used in the n-1 level image. Finally we can get the parameter of lines in the primitive image. Experiments show that this method can extremely reduces the computational time.

scholarly journals Nystagmus Estimation for Dizziness Diagnosis by Pupil Detection and Tracking Using Mexican-Hat-Type Ellipse Pattern Matching

Healthcare ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 885
Author(s):  
Yoanda Alim Syahbana ◽  
Yokota Yasunari ◽  
Morita Hiroyuki ◽  
Aoki Mitsuhiro ◽  
Suzuki Kanade ◽  
...  
Keyword(s):  
Pattern Matching ◽  
Hough Transform ◽  
University Hospital ◽  
Transform Method ◽  
Data Set ◽  
Medical Specialists ◽  
Detection And Tracking ◽  
Mexican Hat ◽  
Pupil Detection ◽  
In The Wild

The detection of nystagmus using video oculography experiences accuracy problems when patients who complain of dizziness have difficulty in fully opening their eyes. Pupil detection and tracking in this condition affect the accuracy of the nystagmus waveform. In this research, we design a pupil detection method using a pattern matching approach that approximates the pupil using a Mexican hat-type ellipse pattern, in order to deal with the aforementioned problem. We evaluate the performance of the proposed method, in comparison with that of a conventional Hough transform method, for eye movement videos retrieved from Gifu University Hospital. The performance results show that the proposed method can detect and track the pupil position, even when only 20% of the pupil is visible. In comparison, the conventional Hough transform only indicates good performance when 90% of the pupil is visible. We also evaluate the proposed method using the Labelled Pupil in the Wild (LPW) data set. The results show that the proposed method has an accuracy of 1.47, as evaluated using the Mean Square Error (MSE), which is much lower than that of the conventional Hough transform method, with an MSE of 9.53. We conduct expert validation by consulting three medical specialists regarding the nystagmus waveform. The medical specialists agreed that the waveform can be evaluated clinically, without contradicting their diagnoses.

Coarse-To-Fine 3D Randomized Hough Transform for Dim Target Detection

2014 ◽  
Vol 519-520 ◽  
pp. 1040-1045
Author(s):  
Ling Fan
Keyword(s):  
Target Detection ◽  
Hough Transform ◽  
Constant Velocity ◽  
Three Dimensional ◽  
Randomized Hough Transform ◽  
Straight Line ◽  
Memory Complexity ◽  
Coarse To Fine

This paper makes some improvements on Roberts representation for straight line in space and proposes a coarse-to-fine three-dimensional (3D) Randomized Hough Transform (RHT) for the detection of dim targets. Using range, bearing and elevation information of the received echoes, 3D RHT can detect constant velocity target in space. In addition, this paper applies a coarse-to-fine strategy to the 3D RHT, which aims to solve both the computational and memory complexity problems. The validity of the coarse-to-fine 3D RHT is verified by simulations. In comparison with the 2D case, which only uses the range-bearing information, the coarse-to-fine 3D RHT has a better practical value in dim target detection.

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