Vision-based online detection system of support bar

Hu, Chao; Yu, Zehui; Cui, Jialin; You, Xiaohe

doi:10.1109/icinfa.2016.7832073

Cited by 2 publications

(2 citation statements)

References 6 publications

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“…In order to meet the needs of online measurement, a single-lens mode using monochromatic light was proposed to avoid the influence of ambient light and the reflection characteristics of the measured part. In 2016, Chen et al [8] studied the detection system for automobile oil support rods of using machine vision, which has been put into the market. In 2017, Huang and Chen [9] adopted a pulse coupled neural network (PCNN) for edge detection and recognition, which preliminarily proposed the automatic recognition and detection system of machine vision, and carried out detection and recognition experiments on small parts such as relay covers.…”

Section: Introductionmentioning

confidence: 99%

Research on Both the Classification and Quality Control Methods of the Car Seat Backrest Based on Machine Vision

Sun

Jian-ping

Zhu

et al. 2022

Wireless Communications and Mobile Computing

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In order to solve the problems of slow manual inspection speed and low fault detection accuracy of car seat back parts, this article using Q company’s car seat back parts researches and designs a car seat back classification and quality inspection screening system. Firstly, SURF (speeded up robust features) is combined with the CNN (convolutional neural network) to classify three types of car seat backrests: A, B, and C. Then, to establish the spring hook angle detection model of the car seat back to detect the misfitting and omission of the Class A car seat back springs, experimental results showed that the neural network-based car seat back detection method proposed in this paper had a feature point mismatch rate, which is less than 1.5% in the classification and recognition of car seat backs. The recognition rate of the training sample was 100% and that of the test sample was 99.56%. The accuracy rate of detection when inspecting 50 car seat backrests reached 98%, and the test results showed that the system can effectively reduce labor costs and improve the detection efficiency of auto parts.

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Section: Introductionmentioning

confidence: 99%

Research on Both the Classification and Quality Control Methods of the Car Seat Backrest Based on Machine Vision

Sun

Jian-ping

Zhu

et al. 2022

Wireless Communications and Mobile Computing

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show abstract

“…For example, a highspeed and high precision smoothness detection system is required for efficient operation in ceramic production industry [1]. An online computer-vision based structural problem detection system is proposed in [2] for automotive industry applications, in order to increase reliability and safety. In telecommunications, online trigger systems are required, for example, to detect anomalies and non-authorized access [3].…”

Section: Introduction Ementioning

confidence: 99%

Embedded Signal Processing Module for Online Filtering in High-Event Rate Conditions

Esteves

Filho

Farias

et al. 2018

JCIS

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Abstract-Online event detection (filtering) is required in communications, industry and electronic instrumentation systems. Those systems may comprise sequential decision levels. Eventually, decision to reject or accept an event may comprise fusion of different measured data. This work describes an embedded solution in field-programmable gate array (FPGA), which allows to combine information from two different sources for a decision. A matched filter discriminator was used to identify typical signatures of interest. The main focus is on both digital data control and packaging module design and implementation and optimization of the matched filter module in terms of FPGA occupation. The proposed digital electronic system is presented and simulation results are used to validate the design.Index Terms-Online event filtering, embedded digital signal processing, FPGA, matched filter, electronic instrumentation.

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Vision-based online detection system of support bar

Cited by 2 publications

References 6 publications

Research on Both the Classification and Quality Control Methods of the Car Seat Backrest Based on Machine Vision

Research on Both the Classification and Quality Control Methods of the Car Seat Backrest Based on Machine Vision

Embedded Signal Processing Module for Online Filtering in High-Event Rate Conditions

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