Limited Length and Limited Weight Intelligent Cutting System Based on Image Pattern Recognition and Closed Loop Feedback Device

2014 ◽  
Vol 644-650 ◽  
pp. 4463-4466
Author(s):  
Yan Li Zuo ◽  
Xiao Fen Guo
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Long Distance ◽  
Loop Feedback ◽  
Limited Length ◽  
Cutting System ◽  
Image Pattern ◽  
Increase Success Rate

Rough cutting section and excess error will cause more waste and increase cost. This paper studies pattern recognition and image processing, proposes a method to implement limited length and limited weight cutting with pattern recognition and image processing technique. The experiment results show that the system is satisfactory in operation, maintenance, cutting precision, processes levels and rates of finished products. Collecting work field’s data with cameras from long-distance, this method will not only reduce the possibility for people to work in the bad circumstance, but also operate more expediently and more reliably, making the equipment and the worker safer. Strong anti-jamming can recognize the steel well and truly with these techniques. It can reduce the length error from 80mm to 10~15mm, so it can reduce product cost, and increase success rate of the finished product.

scholarly journals Health Detection of Wheat Crop Using Pattern Recognition and Image Processing

2020 ◽  
Vol 15 (2) ◽  
pp. 50-60 ◽  
Author(s):  
Balwant Ram ◽  
Mamoon Rashid ◽  
Kamlesh Lakhwani ◽  
Shibi S. Kumar
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Human Resources ◽  
Agricultural Sector ◽  
Value Added ◽  
Processing Technique ◽  
Vital Role ◽  
Image Processing Technique ◽  
Wheat Crop ◽  
Recognition Method

Agriculture plays a vital role in India's economy. 44% of the employment in India is engaged in agriculture and allied activities and it also contributes 17% of the gross value added. As most of the country's people are in the agricultural sector and out of them only a few are literate about how to protect their cultivation ultimately gives rise to severe problems like a low economy in the sector and starvation for the nation. The job of this research is to help the farmers to save crops from disease. The authors came with the thought of combining a pattern recognition method and an image processing technique. The system allows a farmer to follow a particular pattern of growing crops so that threats will be analyzed earlier. Combining this with the power of Internet of Things, the authors can automate the process without the need for human resources. This research can ultimately make the agriculture process faster and farmers can cultivate more in a less amount of time.

scholarly journals Pattern Recognition through Dip for Wind Turbine

2020 ◽  
Vol 9 (6) ◽  
pp. 448-450
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Wind Turbine ◽  
Digital Image Processing ◽  
Video Stream ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Test Items ◽  
Digital Image Processing Technique ◽  
Proposed Model

This paper depicts the realization of DIP (Digital Image Processing) technique for pattern recognition to identify objects in video stream. The proposed model compares the test object with standard model and identifies the missing objects in the test item. The model uses image classifier algorithm as a tool. The simulations are carried out in MATLab Simulink and various test items are compared under different morphological conditions. The model is fabricated to analyze and indicate the omitted components in wind turbine.

scholarly journals Precise levelling in crossing river over 5 km using total station and GNSS

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
DingLiang Yang ◽  
JinGui Zou
Keyword(s):  
Image Processing ◽  
Processing Technique ◽  
Angle Measurement ◽  
Second Order ◽  
Image Processing Technique ◽  
Long Distance ◽  
River Bank ◽  
Total Station ◽  
Pixel Image ◽  
Reciprocal Method

AbstractThe trigonometric levelling using the simultaneous reciprocal method has been proved to meet the precision of second order levelling. But this method is invalid once the distance of river crossing is beyond 3.5 km due to the difficulty of target recognition at such a long distance. To expand the available range of this method, this paper focuses on solving the target aiming and distance observation over a long distance. A modular LED 5-prism (modified Leica GPR1 reflector) as an illuminated target instead of the common prism is introduced, and we adopt the sub-pixel image processing technique to recognize the center of the target image pictured by image assisted total station (Leica Nova TM50 I equipped with a coaxial camera). Based on the principle of precise trigonometric levelling, this paper utilizes two image assisted total stations using image processing technique to perform simultaneous reciprocal for zenith angle measurement and GNSS static measurement for slope distance measurement to determine the height difference of either river bank. And long-distance precise river-crossing levelling can be realized based on the mentioned above. Besides, it is successful to apply in the experiment of Fuzhou Bridge spanning 6.3 km in China. The result shows the standard deviation is ± 0.76 mm/km that is compatible with the precision of second order levelling has.

Automatic Number Plate Goyal Recognition-Image Processing Technique

2016 ◽  
Vol 10 (2) ◽  
Author(s):  
Priti Rajvanshi ◽  
Vijaypal Singh Dhaka
Keyword(s):  
Artificial Intelligence ◽  
Image Processing ◽  
Pattern Recognition ◽  
Mathematical Morphology ◽  
Geometric Analysis ◽  
Processing Technique ◽  
Image Processing Technique ◽  
License Plate ◽  
License Plate Recognition ◽  
Recognition Systems

Automated Number Plate Recognition (ANPR) is also known as Automated License Plate Recognition (ALPR).Automatic Number Plate Recognition or ANPR is a technology that uses pattern recognition to ‘read’ vehiclenumber plates. The design of ANPR systems is a field of research in artificial intelligence and pattern recognition. The main goal of this paper is to study algorithmic and mathematical principles of automatic number plate recognition systems. ANPR can be used to store the images captured by the cameras as well as the text from the number plate and using mathematical morphology methods to detect the edges of the rectangular plate. Mathematical morphology is a part of digital image processing which is concerned withimage filtering and geometric analysis by using structuring elements (SE).

Automatic Number Plate Recognition- Image Processing Technique

2016 ◽  
Vol 11 (01) ◽  
Author(s):  
Priti Rajvanshi Goyal ◽  
Vijaypal Singh Dhaka
Keyword(s):  
Artificial Intelligence ◽  
Image Processing ◽  
Pattern Recognition ◽  
Mathematical Morphology ◽  
Geometric Analysis ◽  
Processing Technique ◽  
Image Processing Technique ◽  
License Plate ◽  
License Plate Recognition ◽  
Recognition Systems

Automated Number Plate Recognition (ANPR) is also known as Automated License Plate Recognition (ALPR). Automatic Number Plate Recognition or ANPR is a technology that uses pattern recognition to ‘read’ vehicle number plates. The design of ANPR systems is a field of research in artificial intelligence and pattern recognition. The main goal of this paper is to study algorithmic and mathematical principles of automatic number plate recognition systems. ANPR can be used to store the images captured by the cameras as well as the text from the number plate and using mathematical morphology methods to detect the edges of the rectangular plate. Mathematical morphology is a part of digital image processing which is concerned with image filtering and geometric analysis by using structuring elements (SE).

A New Image Processing Technique for STEM

1974 ◽  
Vol 32 ◽  
pp. 432-433
Author(s):  
Yasushi Kokubo ◽  
Hirotami Koike ◽  
Teruo Someya
Keyword(s):  
Electron Microscopy ◽  
Image Processing ◽  
Scanning Electron Microscopy ◽  
Elastic Scattering ◽  
Field Emission ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Energy Analyzer ◽  
Scanning Microscope ◽  
Scanning Electron

One of the advantages of scanning electron microscopy is the capability for processing the image contrast, i.e., the image processing technique. Crewe et al were the first to apply this technique to a field emission scanning microscope and show images of individual atoms. They obtained a contrast which depended exclusively on the atomic numbers of specimen elements (Zcontrast), by displaying the images treated with the intensity ratio of elastically scattered to inelastically scattered electrons. The elastic scattering electrons were extracted by a solid detector and inelastic scattering electrons by an energy analyzer. We noted, however, that there is a possibility of the same contrast being obtained only by using an annular-type solid detector consisting of multiple concentric detector elements.

A Comparative Study of Ant and Genetic Algorithms in Digital Mammography

2018 ◽  
pp. 194-200
Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Medical Image ◽  
Medical Image Processing ◽  
Processing Technique ◽  
Input Image ◽  
Image Processing Technique ◽  
Computational Time ◽  
Image Mining ◽  
The Individual

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.

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