Machine Vision Row Crop Detection Using Blob Analysis and the Hough Transform

2013 ◽  
Author(s):  
F. Rovira-Más ◽  
Q. Zhang ◽  
J. F. Reid and J. D. Will
Keyword(s):  
Machine Vision ◽  
Hough Transform ◽  
Row Crop ◽  
Blob Analysis

Identification of the Hook on Investment Casting Shell Line Based on Machine Vision

2012 ◽  
Vol 220-223 ◽  
pp. 1356-1361
Author(s):  
Xi Jie Tian ◽  
Jing Yu ◽  
Chang Chun Li
Keyword(s):  
Machine Vision ◽  
Investment Casting ◽  
Hough Transform ◽  
Image Matching ◽  
Feature Matching ◽  
Image Acquisition ◽  
Target Range ◽  
Target Area ◽  
Matching Method ◽  
Vertical Projection

In this paper, the idea identify the hook on investment casting shell line based on machine vision has been proposed. According to the characteristic of the hook, we do the image acquisition and preprocessing, we adopt Hough transform to narrow the target range, and find the target area based on the method combining the level projection and vertical projection, use feature matching method SIFT to do the image matching. Finally, we get the space information of the target area of the hook.

Detection for Weak Navigation Line for Wheat Planter Based on Machine Vision

2012 ◽  
Vol 246-247 ◽  
pp. 235-240
Author(s):  
Yang Liu ◽  
Bing Qi Chen
Keyword(s):  
Wavelet Transform ◽  
Machine Vision ◽  
Hough Transform ◽  
Processing Time ◽  
Linear Analysis ◽  
Operating Environment ◽  
Natural Conditions ◽  
Ridge Line ◽  
Navigation Information ◽  
Regional Boundary

In order to realize automatic operation for a wheat planter in a field, an algorithm was developed in the research to detect navigation line under sowing operating environment with weak navigation information based on machine vision. Wavelet transform, linear analysis and front and rear frame interrelated were used to get candidate points at regional boundary in the image. Then linear fitting of the candidate points was carried out using the Passing a Known Point Hough Transform. Sowing videos captured under different natural conditions, in different regions were used to test the performance of the algorithm. Results show that the algorithm is able to detect ridge line, sowing line and field end accurately, steadily and quickly, the average processing time for each frame is about 30ms.

Machine Vision for Tool Status Monitoring in Turning Inconel 718 using Blob Analysis

2015 ◽  
Vol 2 (4-5) ◽  
pp. 1841-1848 ◽  
Author(s):  
Y.D. Chethan ◽  
H.V. Ravindra ◽  
Y.T.Krishne gowda ◽  
S. Bharath Kumar
Keyword(s):  
Machine Vision ◽  
Inconel 718 ◽  
Status Monitoring ◽  
Blob Analysis

Research on the Algorithm of Automatic Detection of Bus Dashboard Pointer Based on CM-Hough Transforms

2014 ◽  
Vol 621 ◽  
pp. 663-668
Author(s):  
Peng Ge Ma ◽  
Rong Xing Guo
Keyword(s):  
Machine Vision ◽  
Hough Transform ◽  
Detection System ◽  
Automatic Detection ◽  
Detection Experiment ◽  
Position Detection ◽  
Image Analysis Algorithm ◽  
Hough Transforms ◽  
Working Principle ◽  
Automatic Detection System

The pointer position detection is an important part of implementing the bus dashboard functional test using machine vision. This paper introduces the composition and working principle of the dashboard automatic detection system on machine vision. Then, combining with image processing and Hough transform, we get the image analysis algorithm of the dashboard pointer detection. By analyzing a large amount of computation resulted from the fact that traditional Hough transform uses divergent mapping methods, paper puts forward the methods of improving the convergence of the mapping and conducts parameter space mapping, which effectively reduces the amount of computation. After that, combining with the actual picture of a bus dashboard, automatic detection experiment was carried out for the proposed algorithm. Experiments show that algorithm for dashboard pointer position machine visual based on CM-Hough transform can obtain the angle of the pointer, and effectively shorten the time for dashboard functionality test, and improve the efficiency of the production line for passenger bus dashboard.

High-precision alignment system of machine vision based on Hough transform

2017 ◽  
Vol 38 (6) ◽  
pp. 523-526
Author(s):  
Wei Li ◽  
Guo Yujing ◽  
Lu Xiangning
Keyword(s):  
Machine Vision ◽  
High Precision ◽  
Hough Transform ◽  
Alignment System

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.

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