Design of vision detection algorithm and system for BGA welding balls

2018 ◽  
Vol 26 (9) ◽  
pp. 2190-2197
Author(s):  
罗志伟 LUO Zhi-wei ◽  
杨玉龙 YANG Yu-long ◽  
李志红 LI Zhi-hong
Keyword(s):  
Detection Algorithm ◽  
Vision Detection

Application of Least Square Algorithm for Ellipses Detection

2012 ◽  
Vol 532-533 ◽  
pp. 1527-1531
Author(s):  
Can Yuan ◽  
Chen Wang ◽  
Gang Liu
Keyword(s):  
Randomized Algorithm ◽  
Detection Algorithm ◽  
Image Features ◽  
Least Square ◽  
Complex Environment ◽  
Hough Transforms ◽  
Significant Process ◽  
Least Square Approach ◽  
Stability And Accuracy ◽  
Vision Detection

It is a significant process to automatically extract ellipses or elliptic image features in highly precise vision detection, especially to achieve rapid as well as accurate detection in complex environment. Fortunately, this paper provides an approach to solve the problem. We firstly detect the edge of images by using sub-pixel edge detection algorithm, and then determine the elliptical shapes, and eliminate the non-ellipses. For the complicated context and taking into account the occlusion of ellipses, we integrate the robust Hough transforms and slip window into randomized algorithm based on least square approach with the purpose of having got the veracious ellipse parameters, which proves that the approach is available for images in stability and accuracy.

Study of Pose Detection Algorithm for Specific Object Based on Monocular Vision

2014 ◽  
Vol 651-653 ◽  
pp. 517-523 ◽  
Author(s):  
Ling Yun Liu ◽  
Min Luo ◽  
Yue Min Wu
Keyword(s):  
Hausdorff Distance ◽  
Image Plane ◽  
Mathematic Model ◽  
Detection Algorithm ◽  
Monocular Vision ◽  
Threshold Method ◽  
Virtual Camera ◽  
Pose Detection ◽  
Specific Object ◽  
Vision Detection

This paper brings forward a monocular vision detection algorithm in allusion to the specific object’s pose based on Hausdorff Distance. At first, according to the mathematic model which has been established, the 2D template sequence is generated by projecting the specific object in different poses into the image plane of a virtual camera. Then, in order to predigest calculations and accelerate the matching speed during the image matching, the algorithm adopts the local-mean Hausdorff Distance as matching estimate and adopts the search strategy based on hiberarchy which reduces the searching rang by the threshold method before accurate match. In the end of this paper, the experiment that measures the poses of the clamp via the different clamp images respectively is given to testify the validity and speediness of this algorithm.

Research on detection algorithm of lithium battery surface defects based on embedded machine vision

2021 ◽  
pp. 1-9
Author(s):  
Yonggang Chen ◽  
Yufeng Shu ◽  
Xiaomian Li ◽  
Changwei Xiong ◽  
Shenyi Cao ◽  
...  
Keyword(s):  
Lithium Battery ◽  
Surface Defects ◽  
Visual Detection ◽  
Rapid Development ◽  
Detection Algorithm ◽  
Large Error ◽  
Detection Algorithms ◽  
Manual Inspection ◽  
Low Efficiency ◽  
Vision Detection

In the production process of lithium battery, the quality inspection requirements of lithium battery are very high. At present, most of the work is done manually. Aiming at the problem of large manual inspection workload and large error, the robot visual inspection technology is applied to the production of lithium battery. In recent years, with the rapid development and progress of science and technology, the rapid development of visual detection hardware and algorithms, making it possible to screen defective products through visual detection algorithms. This paper takes lithium battery as the research object, and studies its vision detection algorithm. As a common commodity, the quality of lithium battery is the key for users to choose. With the increasing requirements of users for battery quality, how to produce high-quality battery is the key problem to be solved by manufacturers. However, at present, the defects of battery surface are mostly carried out manually. There are low efficiency and low detection rate in the process of manual detection. In this paper, the visual detection algorithm is studied to detect the defects such as pits, rust marks and broken skin on the surface of lithium battery, specifically to design the imaging experimental platform of lithium battery; use different lighting schemes to design different battery positioning and extraction algorithms; use Hough detection method to locate the battery surface, and design the battery defect algorithm for this, and compare the algorithm through experiments.

scholarly journals Truck-Lifting Prevention System Based on Vision Tracking for Container-Lifting Operation

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Qingfeng Huang ◽  
Yage Huang ◽  
Zhiwei Zhang ◽  
Yujie Zhang ◽  
Weijian Mi ◽  
...  
Keyword(s):  
Measurement Accuracy ◽  
Detection Algorithm ◽  
Container Terminals ◽  
Multitarget Tracking ◽  
Detection And Tracking ◽  
Prevention System ◽  
Accident Detection ◽  
Vision Detection ◽  
Lifting Equipment ◽  
Traditional Image

Truck-lifting accidents are common in container-lifting operations. Previously, the operation sites are needed to arrange workers for observation and guidance. However, with the development of automated equipment in container terminals, an automated accident detection method is required to replace manual workers. Considering the development of vision detection and tracking algorithms, this study designed a vision-based truck-lifting prevention system. This system uses a camera to detect and track the movement of the truck wheel hub during the operation to determine whether the truck chassis is being lifted. The hardware device of this system is easy to install and has good versatility for most container-lifting equipment. The accident detection algorithm combines convolutional neural network detection, traditional image processing, and a multitarget tracking algorithm to calculate the displacement and posture information of the truck during the operation. The experiments show that the measurement accuracy of this system reaches 52 mm, and it can effectively distinguish the trajectories of different wheel hubs, meeting the requirements for detecting lifting accidents.

A Vision Detection Algorithm for LIGA Part Assembly

2013 ◽  
Vol 325-326 ◽  
pp. 1271-1275 ◽  
Author(s):  
Jun Gao ◽  
Xin Ye ◽  
Zhi Jing Zhang ◽  
Yong Long Tang ◽  
Xin Jin
Keyword(s):  
Feature Recognition ◽  
Recognition Accuracy ◽  
Detection Algorithm ◽  
Recognition Algorithm ◽  
Maximum Information ◽  
Assembly Feature ◽  
Maximum Information Entropy ◽  
Vision Detection ◽  
Edge Recognition

This paper proposes a vision detection algorithm to acquire LIGA part’s edges based on an in-house multi-DOF manipulator for LIGA part assembly. Feature recognition based on maximum information entropy is proposed to solve the problem that high precision edge recognition under backlight source. In order to further improve vision recognition accuracy, edge feature recognition algorithm based on symmetrical edge is proposed to recognize the center line of the symmetrical parts when the quality of the image is poor.

The Research on a Rapid Appearance Detection Method for Vertical Polarized Electrolytic Capacitors

2013 ◽  
Vol 415 ◽  
pp. 333-337
Author(s):  
Min Dai ◽  
Chen Yang Wang ◽  
Kai Chen ◽  
Zhi Sheng Zhang
Keyword(s):  
Processing Speed ◽  
Detection Method ◽  
Low Cost ◽  
Detection Algorithm ◽  
Feature Points ◽  
Electrolytic Capacitors ◽  
Fast Processing ◽  
High Production ◽  
Vision Detection ◽  
Rapid Appearance

For detecting the defects of the vertical polarized electrolytic capacitors in the process of production, an online machine vision detection method based on DSP is proposed in this paper. The hardware framework is designed emphatically with DM642 as the core processor, which has the advantages of small size, fast processing speed, low cost and low power consumption. The software workflow of the capacitors defects detection is introduced. To meet the requirement of high production and real-time detection of capacitors, a rapid appearance detection algorithm is introduced by using a few number of feature points instead of the whole. The experimental results show that the proposed method can achieve many types of defects detection of the capacitors.

Research on Real-Time Vision Detection Method for Sanitary Labels

2013 ◽  
Vol 300-301 ◽  
pp. 484-489
Author(s):  
Chao Luo ◽  
Le Song ◽  
Mei Rong Zhao ◽  
Yu Chi Lin ◽  
Jian Li
Keyword(s):  
Real Time ◽  
Template Matching ◽  
Detection Method ◽  
Detection System ◽  
Recognition Rate ◽  
Detection Algorithm ◽  
Inspection System ◽  
Matching Method ◽  
Accurate Identification ◽  
Vision Detection

Taking diaper which is a representative production of sanitary supplies as an example, a real-time detection method for diaper label based on machine vision is developed. To identify the location of diaper surface label position rapidly, a visual inspection system platform applies to production line is built. Images are captured with high-resolution colorful CCD industrial camera and NC template matching method is adopted as the surface label detection algorithm. Meanwhile, the comparative experiments results among NC, ABS method and Moment Matching method are presented. Experimental results show that this label detection system can realize accurate identification on the condition of different light, whose recognition rate can reach up to 97% and detection algorithm is of preferable instantaneity and stability.

scholarly journals Research on Visual Detection Algorithm of 500kV High Voltage Live Operating Robot

2021 ◽  
Vol 2087 (1) ◽  
pp. 012093
Author(s):  
Suping Guo ◽  
Jun Deng ◽  
Yahui Fan ◽  
Sijing Dai
Keyword(s):  
Transmission Line ◽  
High Voltage ◽  
Visual Detection ◽  
Detection Algorithm ◽  
Operating Efficiency ◽  
Detection Technology ◽  
Power Operation ◽  
Low Efficiency ◽  
Working Device ◽  
Vision Detection

Abstract The 500kV transmission line is exposed to the outdoor for a long time. It is affected by complex climate charge change and other factors which leads to line connection parts bolt loosening, wire breaking and fixture damage and other line failures. In order to ensure the stable transmission of electric energy, power operators need to wear shielding suits and work in the high-risk and high-voltage environment. Use of electric power operation robot instead of manual operation is an effective way to liberate maintenance staff labor. But robots still have some problems such as low degree of automation and low efficiency of power operation. Machine vision detection technology in recent years has been widely used in major areas including deep learning as emerging visual detection technology shows excellent performance. In this paper, the vision detection algorithm is studied respectively for the bolt fastening end working device and wire repairing end working device of the live transmission line robot to improve the operating efficiency of the robot.

Read, Understand, Learn, & Excel: Development and Testing of an Automated Reading Strategy Detection Algorithm for Postsecondary Students

2019 ◽  
Vol 28 (3) ◽  
pp. 1257-1267 ◽  
Author(s):  
Priya Kucheria ◽  
McKay Moore Sohlberg ◽  
Jason Prideaux ◽  
Stephen Fickas
Keyword(s):  
Academic Success ◽  
Undergraduate Students ◽  
Expository Text ◽  
Reading Strategy ◽  
Detection Algorithm ◽  
Expository Texts ◽  
Human Observer ◽  
Behavioral Strategies ◽  
Periodic Review ◽  
Wide Range

PurposeAn important predictor of postsecondary academic success is an individual's reading comprehension skills. Postsecondary readers apply a wide range of behavioral strategies to process text for learning purposes. Currently, no tools exist to detect a reader's use of strategies. The primary aim of this study was to develop Read, Understand, Learn, & Excel, an automated tool designed to detect reading strategy use and explore its accuracy in detecting strategies when students read digital, expository text.MethodAn iterative design was used to develop the computer algorithm for detecting 9 reading strategies. Twelve undergraduate students read 2 expository texts that were equated for length and complexity. A human observer documented the strategies employed by each reader, whereas the computer used digital sequences to detect the same strategies. Data were then coded and analyzed to determine agreement between the 2 sources of strategy detection (i.e., the computer and the observer).ResultsAgreement between the computer- and human-coded strategies was 75% or higher for 6 out of the 9 strategies. Only 3 out of the 9 strategies–previewing content, evaluating amount of remaining text, and periodic review and/or iterative summarizing–had less than 60% agreement.ConclusionRead, Understand, Learn, & Excel provides proof of concept that a reader's approach to engaging with academic text can be objectively and automatically captured. Clinical implications and suggestions to improve the sensitivity of the code are discussed.Supplemental Materialhttps://doi.org/10.23641/asha.8204786

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