The Assembly Error Detection of Automotive Airbag Based on Machine Vision

2015 ◽  
Vol 738-739 ◽  
pp. 694-698
Author(s):  
Xiao Dong Wang ◽  
Qi Liu ◽  
Wei Zhang

Based on the principle of machine vision technology, we designed a methodto detect the outline dimensions of automotive airbag quickly and accurately. We Used CCD camera obtain the airbag image, through the image processing method ofsmooth filtering andgray-scale transformationto complete pre-processing, finally applied Canny edge detection operator to extract the boundary of the airbag contour features,and then took the template matching methodto detect assemble error of the airbag image whether meet the requirement.The results show that the detection method have a higher precision, and the time is very short, it can improve the sampled positioningerror detection for the all checks image recognition detection, suitable for application in real-time online detection of airbag assembly line.


2013 ◽  
Vol 32 (8) ◽  
pp. 2296-2298 ◽  
Author(s):  
Fan ZHANG ◽  
Zhong-wei PENG ◽  
Shui-jin MENG


2021 ◽  
Vol 2089 (1) ◽  
pp. 012008
Author(s):  
B Padmaja ◽  
P Naga Shyam Bhargav ◽  
H Ganga Sagar ◽  
B Diwakar Nayak ◽  
M Bhushan Rao

Abstract Visually impaired and senior citizens find it difficult to identify different banknotes, driving the need for an automated system to recognize currency notes. This study proposes recognizing Indian currency notes of various denominations using Deep Learning through the CNN model. While not recognizing currency notes is one issue, identifying fake notes is another major issue. Currency counterfeiting is the illegal imitation of currency to deceive its recipient. The current existing methodologies for identifying a phony note rely on hardware. A method completely devoid of hardware that relies on specific security features to help distinguish a legitimate currency note from an illegitimate one is much needed. These features are extracted using the boundary box region of interest (ROI) and Canny Edge detection in OpenCV implemented in Python, and the multi scale template matching algorithm is applied to match the security features and differentiate fake notes from legitimate notes.



2011 ◽  
Vol 145 ◽  
pp. 547-551 ◽  
Author(s):  
Zahari Taha ◽  
Jessnor Arif Mat Jizat

In this paper a comparison of two approaches for collision avoidance of an automated guided vehicle (AGV) using monocular vision is presented. The first approach is by floor sampling. The floor where the AGV operates, is usually monotone. Thus, by sampling the floor, the information can be used to search similar pixels and establish the floor plane in its vision. Therefore any other objects are considered as obstacles and should be avoided. The second approach employs the Canny edge detection method. The Canny edge detection method allows accurate detection, close to real object, and minimum false detection by image noise. Using this method, every edge detected is considered to be part of an obstacle. This approach tries to avoid the nearest obstacle to its vision. Experiments are conducted in a control environment. The monocular camera is mounted on an ERP-42 Unmanned Solution robot platform and is the sole sensor providing information for the robot about its environment.



2012 ◽  
Vol 616-618 ◽  
pp. 1993-1996
Author(s):  
Yu Zhuo Men ◽  
Hai Bo Yu ◽  
Hua Wang ◽  
Jin Gang Gao ◽  
Xin Pan

On-line detection method for automobile frame side rail process holes is proposed in this articled. It is achieved by virtue of machine vision technology detection method. Many images captured by CCD camera are processed and analyzed to finally complete the automatic detection of automobile chassis frame process holes. Machine vision technology is applied to achieve the on-line detection of machining quality of frame side rail mounting holes. The developed detection system prototype has very high detection accuracy.



Author(s):  
Jyoti Malik ◽  
Ratna Dahiya ◽  
Dhiraj Girdhar ◽  
G. Sainarayanan


Author(s):  
S-H Chen ◽  
T-T Liao ◽  
C-T Chen

This study presents a rapid and reliable machine vision technique for measuring the principal features of interest in an integrated circuit carrier tape, namely the diameters of the circular sprocket perforations and centre hole, the width of the carrier tape, and the width and length of the centre cavity. In performing the measurement process, the quality of the image acquisition process is enhanced by using two auxiliary light sources to suppress the effects of natural variations in the environmental lighting conditions. Having acquired the image using a charge coupled device (CCD) camera, the features of interest are separated from the background region of the image using a two-threshold algorithm based on the Otsu threshold selection method. The edge of each feature is then extracted from the binary image using the Canny edge detection method. The dimensions of the circular features are obtained by fitting four right-angle triangles within the periphery of the extracted circular edge and then computing the circle diameter by taking the mean of the hypotenuse values of the four triangles as computed using the Pythagorean theorem.



2013 ◽  
Vol 658 ◽  
pp. 546-550
Author(s):  
Xiao Dong Wang ◽  
Xiao Wei Chen ◽  
Wei Zhang ◽  
Bo Liu ◽  
Liang Dong An

In this paper we have developed a new methodology for detecting the contour size of driver airbag based on image processing technology and Machine vision. Through the CCD camera we can obtain the image, and then do the following operations by a computer, such as binarization, edge extraction and so on the other image preprocessing. This methodology uses intelligent template matching technology to detect the airbags and by comparing with the predefined parameter to determine whether the contour size is qualified .The experimental results show that: this new detection method solves the disadvantage of traditional detection method, such as the low detection efficiency, the detection precision is not high, the poor detection repeatability, the higher rate of detection miscarriage of justice.



2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Oktaf Brillian Kharisma

Sistem identifikasi pajak kendaraan berdasarkan plat nomor untuk memudahkan pendataan dalam penerapan regulasi pemutasian kendaraan disuatu wilayah sangatlah penting. Kasus di provinsi Riau, kendaraan yang beroperasi melebihi 3 bulan di luar wilayah diwajibkan segera memutasi pajak kendaraannya. Identifikasi masih dilakukan secara manual dengan melibatkan orang untuk melakukan pendataan. Sehingga, kurang efektif dan efisien. Tujuan penelitian untuk menghasilkan sistem yang memudahkan dalam mengidentifikasi dan mengumpulkan data plat nomor kendaraan untuk pajak daerah menggunakan algoritma canny edge detection dan template matching. Sistem dibuat menggunakan aplikasi GUI Matlab dan hasil langsung dikirim ke aplikasi website. Data video yang di proses beresolusi 1280x720 pixel dengan menghasilkan akurasi identifikasi plat nomor kendaraan mencapai 87,5%.



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