Study on Automated Scrap-Sorting by an Image Processing Technology

2007 ◽  
Vol 26-28 ◽  
pp. 453-456
Author(s):  
Chan Wook Kim ◽  
Hang Goo Kim
Keyword(s):  
Image Processing ◽  
High Speed ◽  
Ferrous Metal ◽  
Processing Technology ◽  
Functional Tests ◽  
Image Processing Technology ◽  
Sorting System

In this study, an automated scrap-sorting system using image processing technology has been designed and examined to automatically sort out specified materials from a mixture, especially Cu and other non-ferrous metal scraps from a mixture of iron scraps. In the functional tests of the system, its efficiency in the separation of Cu scraps from its mixture with Fe ones reaches to 75 % or more at a conveying speed of 20 m/min., and thus it is expected that the system can be commercialized in the industry of shredder makers if an automated sorting system of high speed is realized.

Design and Testing of an On-Line Omnidirectional Inspection and Sorting System for Soybean Seeds

2018 ◽  
Vol 34 (6) ◽  
pp. 1003-1016
Author(s):  
Longzhe Quan ◽  
Tianyu Zhang ◽  
Liran Sun ◽  
Xin Chen ◽  
Zhitong Xu
Keyword(s):  
Image Processing ◽  
Processing Technology ◽  
Design Parameters ◽  
Soybean Seeds ◽  
Surface Information ◽  
Embedded Image Processing ◽  
Image Processing Technology ◽  
On Line ◽  
Sorting System ◽  
Embedded Image

Abstract. At present, the manual grading of soybean seeds is both time consuming and laborious, and detecting the full-surface information of soybean seeds using an existing automatic sorting machine is difficult. To solve this problem, an on-line omnidirectional inspection and sorting system for soybean seeds was developed using embedded image processing technology. According to the principles employed by the system, the surface friction properties and full-surface information such as the shape, texture and color of soybean seeds were adopted in the study. Soybean seeds were inspected and sorted using their full surface information in combination with the embedded image processing technology. Split, worm-eaten, gray-spotted, slightly cracked, moldy and normal soybeans were used to test the system. According to the test results, the optimum design parameters of the preliminary sorting device based on the friction properties were a tilting angle of 12° and a linear velocity of 0.4 m/s. Furthermore, the optimum design parameters of the directional integrated device were a tilting angle of 19° and a linear velocity of 0.45 m/s. The sorting speed was 400 soybeans per minute with 8-channel parallel transmission. The average sorting accuracies were 99.4% for split soybeans, 98.5% for worm-eaten soybeans, 98.5% for gray-spotted soybeans, 97.7% for slightly cracked soybeans, 98.6% for moldy soybeans, and 98.9% for normal soybeans. The overall results suggest that the system can potentially meet the needs of the rapid inspection and automatic sorting of soybean seeds and provide references for research on the alternating rotational motion of granules and on-line collection of full-surface information. Keywords: Embedded image processing technology, Full surface, Granules, Inspection, On-line, Sorting, Soybean seeds.

Based on Digital Image Processing Ore Appraisal Method Research

2013 ◽  
Vol 385-386 ◽  
pp. 1500-1504
Author(s):  
Jiang Tao Huang ◽  
Jian Peng ◽  
Feng Bo Li
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
High Speed ◽  
Mineral Resources ◽  
Processing Technology ◽  
Image Processing Technology ◽  
Wide Range ◽  
Testing Field ◽  
Processing Techniques

with high speed development of the digital image processing technology, and computer image processing technology used in scientific research more and more widely. Mineral, resources and environment, and other fields, image processing technology also has a wide range of applications. This paper is the application of digital image processing techniques to realize to study all the features of ore and automatically recognize ore , pattern recognition method applied to mineral recognition and testing field, so as to achieve the goal of mineral appraisal.

A Detection System of Tool Condition Based on Image Processing Technology

2012 ◽  
Vol 510 ◽  
pp. 375-379
Author(s):  
Xing Yuan Kou ◽  
Chen Sheng Wang ◽  
Lei Li
Keyword(s):  
Image Processing ◽  
High Speed ◽  
Detection System ◽  
Digital Processing ◽  
Processing Technology ◽  
Detection Accuracy ◽  
Size Change ◽  
Tool Condition ◽  
Image Processing Technology ◽  
Processing Solution

This paper focused on introducing a real-time detection system of tool condition based on image processing technology and determined final algorithm after analyzing several different operators of edge detection. Firstly, the system will complete an acquisition of tool image, and transfer it to the computer. Then the image will be processed by some digital processing algorithms. At last, we can get the tool wear according to the size change of a tool. The result of this study showed that the detection system and its image processing solution could give a desired result. The detection accuracy could reach macron level, and the degree of automation could be improved too. So the system can be used to better meet the needs of high precision and high-speed in modern production.

scholarly journals Digital Image Processing Technology in Design and Development of Automatic Sorting System for Energy Meter Recovery

2021 ◽  
Vol 2143 (1) ◽  
pp. 012042
Author(s):  
Hao Hu ◽  
Bo Liu ◽  
Wen Jie Li ◽  
He Liu Sun ◽  
Tang Sen Ni
Keyword(s):  
Neural Network ◽  
Image Processing ◽  
Artificial Neural Network ◽  
Digital Image Processing ◽  
Digital Image ◽  
Processing Technology ◽  
Automatic Sorting ◽  
Image Processing Technology ◽  
Artificial Neural ◽  
Sorting System

Abstract In order to solve the problems of low sorting efficiency and poor quality caused by manual sorting in traditional electricity meter recovery, this study adopts digital image processing technology to construct an automatic sorting system for electricity meter recovery based on artificial neural network. Firstly, the basic requirements of system construction are analyzed in detail, and then the principle and method of image recognition of artificial neural network are introduced in detail. On this basis, an overall framework of automatic sorting of electricity meter recovery is constructed. Finally, the functional modules are designed and applied, and Azure database is built through SQL Server platform, so as to realize the system application of this research. The final application shows that the automatic sorting system constructed by this study has simple interface and easy operation, which can greatly improve the efficiency and quality of the electricity meter recycling and sorting, and has certain practical significance for the development of the state grid industry.

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