scholarly journals Quality Assessment of Beef Using Computer Vision Technology

2020 ◽  
Vol 40 (6) ◽  
pp. 896-907 ◽  
Author(s):  
Md. Faizur Rahman ◽  
Abdullah Iqbal ◽  
Md. Abul Hashem ◽  
Akinbode A. Adedeji
Keyword(s):  
Computer Vision ◽  
Quality Assessment ◽  
Computer Vision Technology

scholarly journals A Review on Computer Vision Technology for Monitoring Poultry Farm – Application, Hardware, and Software

IEEE Access ◽  
2020 ◽  
pp. 1-1
Author(s):  
Nur Syazarin Natasha Abd Aziz ◽  
Salwani Mohd Daud ◽  
Rudzidatul Akmam Dziyauddin ◽  
Mohamad Zulkefli Adam ◽  
Azizul Azizan
Keyword(s):  
Computer Vision ◽  
Poultry Farm ◽  
Computer Vision Technology

scholarly journals Survey of rice seed quality analysis for varietal purity estimation by using image processing techniques

2018 ◽  
Vol 7 (1.7) ◽  
pp. 34
Author(s):  
S. Durai ◽  
C. Mahesh ◽  
T. Sujithra ◽  
A. Suresh
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
South India ◽  
Seed Quality ◽  
Quality Analysis ◽  
Rice Seed ◽  
Two Factors ◽  
Computer Vision Technology ◽  
Processing Techniques ◽  
Varietal Purity

 In south India rice is the major food source and in agriculture, rice production covers more than 70 percentages of entire forming. But in recent the production only from south India not enough to satisfy the need of all, such a huge demand is there. The better production comes from the selection of good seeds. Up to now formers depend on two factors for selecting better seeds, One is the brand which is approved by some quality standards and second one is analyzed manually by experienced people. Both are risky one, we are not pretty much sure the accuracy of analyze. The second one is seeing and feeling. The inspection is not consistent also very time consuming. In the other way we can use computer vision technology to analyze the quality of the seeds. In recent years many of the big industries they are using computer vision technology with Digital Image Processing for many of the applications. In this Paper we are going to discuss the different seed quality analyzing methods and accuracy of result also. Moreover there are different factors and features are there for it, here we are going to study about varietal purity estimation by different methods.

Vehicle Security Distance Control Based on Binocular Parallax Vision

2014 ◽  
Vol 644-650 ◽  
pp. 207-210
Author(s):  
Shuang Liu ◽  
Xiang Jie Kong ◽  
Ming Cai Shan
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
High Precision ◽  
Stereo Matching ◽  
Vision System ◽  
Intelligent Transportation ◽  
Distance Control ◽  
Calibration Methods ◽  
Computer Vision Technology ◽  
Vehicle Security

Binocular parallax vision system is a kind of computer vision technology. Two cameras on different locations can get two different pictures of same object. The space position of the object can be calculated by the parallax information of two different pictures. The binocular parallax vision technology includes cameras calibration, image processing, and stereo matching analysis. The paper will introduce the inside and outside parameters calibration methods, and combing the traffic applications, designed the calibrating scheme. The parameters that obtained according to the scheme can meet the demands of measuring the vehicle distance. The high precision can meet the needs of intelligent transportation vehicles in a security vehicles spacing survey, which is an effective way for measuring the front car distance.

scholarly journals Optical Crackmeter for Retaining Wall in a Landslide Area Using Computer Vision Technology

2021 ◽  
Vol 33 (3) ◽  
pp. 995
Author(s):  
Yu-Chin Chen ◽  
I-Hui Chen ◽  
Jun-Yang Chen ◽  
Miau-Bin Su
Keyword(s):  
Computer Vision ◽  
Retaining Wall ◽  
Landslide Area ◽  
Computer Vision Technology

scholarly journals Automatic Assembly of Bolts and Nuts Based on Machine Vision Recognition

2021 ◽  
Vol 2113 (1) ◽  
pp. 012033
Author(s):  
Haocheng He
Keyword(s):  
Computer Vision ◽  
Production Line ◽  
Recognition System ◽  
Automatic Assembly ◽  
Robot Arm ◽  
Accuracy Improvement ◽  
Automatic Production ◽  
Computer Vision Technology ◽  
Automatic Production Line ◽  
Pixel Scale

Abstract In this study, based on the computer vision technology, we developed a recognition system for nuts positioning to complete the automatic bolt assembly part of the automatic production line. The actual image of the nut was captured by an industrial camera, which would be processed by the following edge detection and Hough circle transformation. After that, the coordinates of the nuts were obtained in the pixel scale. Finally, the real position of nuts would be fed back to the robot arm, according to which the automatic assembly of the bolt would be completed. This computer vision based recognition system is an indispensable part for the efficiency and accuracy improvement of automatic production line.

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