A Table Recognition and Extraction Algorithm in Dongba Character Documents Based on Hough Transform

2020 ◽  
Author(s):  
Yuting Yang ◽  
Houliang Kang
Keyword(s):  
Hough Transform ◽  
Table Recognition ◽  
Extraction Algorithm

Fast Line Extraction Algorithm Based on Improved Hough Transformation

2014 ◽  
Vol 926-930 ◽  
pp. 3612-3615
Author(s):  
Chun Fang Wang
Keyword(s):  
Image Processing ◽  
Machine Vision ◽  
Hough Transform ◽  
Computational Cost ◽  
Automatic Recognition ◽  
Storage Space ◽  
Important Work ◽  
Local Maxima ◽  
Line Extraction ◽  
Extraction Algorithm

Automatic recognition of the line in the image is an important work in the field of machine vision and image processing. Focusing on the problem of the computational cost and large invalid sampling in the line extraction algorithm using standard Hough transform (HT). An improved HT algorithm is proposed to solve these problems. The parameters of the improved algorithm can be reduced to one and the accumulator is operated by setting the tolerance. Then the existence of linear is determined by seting the threshold. The experimental results show that the algorithm not only can effectively solve the problem of local maxima and improves the algorithm speed and reduces the storage space,but also the accuracy of line extraction is improved.

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.

Modified Hough Transform in Problem of Increasing Probability of Target Detection in Electronic Surveillance Systems

2019 ◽  
Vol 24 (3) ◽  
pp. 291-300
Author(s):  
Evgeny I. Minakov ◽  
◽  
Aleksandr V. Meshkov ◽  
Elena O. Meshkova ◽  
◽  
...  
Keyword(s):  
Target Detection ◽  
Hough Transform ◽  
Surveillance Systems ◽  
Electronic Surveillance

GESTURE RECOGNITION SYSTEM FOR NIGERIAN TRIBAL GREETING POSTURES USING SUPPORT VECTOR MACHINE

2020 ◽  
Vol 5 (2) ◽  
pp. 609
Author(s):  
Segun Aina ◽  
Kofoworola V. Sholesi ◽  
Aderonke R. Lawal ◽  
Samuel D. Okegbile ◽  
Adeniran I. Oluwaranti
Keyword(s):  
Support Vector Machine ◽  
Gesture Recognition ◽  
Recognition Rate ◽  
Recognition Task ◽  
Recognition System ◽  
Human Interaction ◽  
Support Vector ◽  
System A ◽  
Extraction Algorithm ◽  
Gaussian Blur

This paper presents the application of Gaussian blur filters and Support Vector Machine (SVM) techniques for greeting recognition among the Yoruba tribe of Nigeria. Existing efforts have considered different recognition gestures. However, tribal greeting postures or gestures recognition for the Nigerian geographical space has not been studied before. Some cultural gestures are not correctly identified by people of the same tribe, not to mention other people from different tribes, thereby posing a challenge of misinterpretation of meaning. Also, some cultural gestures are unknown to most people outside a tribe, which could also hinder human interaction; hence there is a need to automate the recognition of Nigerian tribal greeting gestures. This work hence develops a Gaussian Blur – SVM based system capable of recognizing the Yoruba tribe greeting postures for men and women. Videos of individuals performing various greeting gestures were collected and processed into image frames. The images were resized and a Gaussian blur filter was used to remove noise from them. This research used a moment-based feature extraction algorithm to extract shape features that were passed as input to SVM. SVM is exploited and trained to perform the greeting gesture recognition task to recognize two Nigerian tribe greeting postures. To confirm the robustness of the system, 20%, 25% and 30% of the dataset acquired from the preprocessed images were used to test the system. A recognition rate of 94% could be achieved when SVM is used, as shown by the result which invariably proves that the proposed method is efficient.

Sign in / Sign up

Export Citation Format

Share Document