A Soldering Defect Inspection System of a Special Integrated Circuit Board Based on Computer Vision

2013 ◽  
Vol 650 ◽  
pp. 543-547
Author(s):  
Cong Ling Zhou ◽  
Jun Qiang Wu ◽  
Yong Qiang Wang ◽  
Zeng Pu Xu
Keyword(s):  
Computer Vision ◽  
Defect Detection ◽  
Integrated Circuit ◽  
Visual Inspection ◽  
Ccd Camera ◽  
Structure Design ◽  
Circuit Board ◽  
Inspection System ◽  
Defect Inspection ◽  
Hardware System

This paper introduces a soldering defect inspection system for a special integrated circuit board aided by the computer vision. Space occluder is fixed on this special integrated circuit board, which makes the light blocked from the CCD camera to the chip pins to be inspected. This system can inspect the light blocked soldering defects of the chip pins through the structure design of hardware system and the software system. It is a cheap but automatic soldering defect inspecting system, and can do the soldering defect detection instead of manual visual inspection, and improve the detection speed and stability.

Study and Realization of Camera Wafer Image Fusion Algorithm

2014 ◽  
Vol 484-485 ◽  
pp. 540-546
Author(s):  
Yi Xu
Keyword(s):  
Image Fusion ◽  
Ccd Camera ◽  
Inspection System ◽  
Defect Inspection ◽  
Fusion Algorithm ◽  
Field Range ◽  
Mosaic Image

Image mosaics not only can make the collected several original images regenerate a complete image, but also can correct the error caused by imaging distortion of the original images, which can achieve the objective of rapid and correct mosaic image. The program studies the image mosaics of wafer defect inspection system. For the problem that the field range taken by CCD camera under resolution of wafer defect inspection system is small, which cant get the whole wafer image once and influences the extraction of subsequent defect features, the study demands to add image mosaics to the system.

scholarly journals Computer vision–based automatic rod-insulator defect detection in high-speed railway catenary system

2018 ◽  
Vol 15 (3) ◽  
pp. 172988141877394 ◽  
Author(s):  
Ye Han ◽  
Zhigang Liu ◽  
DJ Lee ◽  
Wenqiang Liu ◽  
Junwen Chen ◽  
...  
Keyword(s):  
Computer Vision ◽  
Defect Detection ◽  
High Speed ◽  
Power Transmission ◽  
Estimation Algorithm ◽  
Inspection System ◽  
High Speed Railway ◽  
Inspection Method ◽  
Railway Systems ◽  
Catenary System

Maintenance of catenary system is a crucial task for the safe operation of high-speed railway systems. Catenary system malfunction could interrupt railway service and threaten public safety. This article presents a computer vision algorithm that is developed to automatically detect the defective rod-insulators in a catenary system to ensure reliable power transmission. Two key challenges in building such a robust inspection system are addressed in this work, the detection of the insulators in the catenary image and the detection of possible defects. A two-step insulator detection method is implemented to detect insulators with different inclination angles in the image. The sub-images containing cantilevers and rods are first extracted from the catenary image. Then, the insulators are detected in the sub-image using deformable part models. A local intensity period estimation algorithm is designed specifically for insulator defect detection. Experimental results show that the proposed method is able to automatically and reliably detect insulator defects including the breakage of the ceramic discs and the foreign objects clamped between two ceramic discs. The performance of this visual inspection method meets the strict requirements for catenary system maintenance.

scholarly journals A NOVEL METHOD FOR INSPECTION DEFECTS IN COMMERCIAL EGGS USING COMPUTER VISION

2021 ◽  
Vol XLIII-B2-2021 ◽  
pp. 809-816
Author(s):  
Y. M. Valencia ◽  
J. J. Majin ◽  
V. B. Taveira ◽  
J. D. Salazar ◽  
M. E. Stivanello ◽  
...  
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Visual Inspection ◽  
Working Hours ◽  
Inspection System ◽  
Learning Approaches ◽  
Visual Fatigue ◽  
Long Working Hours ◽  
Novel Method ◽  
Classical Image

Abstract. The objective of this work is to compare the use of classical image processing approaches with deep learning approaches in a visual inspection system for defects in commercial eggs. Currently, many industries perform the detection of defects in eggs manually, this implies a large number of workers with long working hours who are exposed to visual fatigue and physical and mental discomfort. As a solution, this work proposes to develop an automatic inspection technique for defects in eggs using computer vision, capable of being operable in the industry. Different image processing approaches were evaluated in order to determine the best solution in terms of performance and processing time.

scholarly journals Implementasi Adaptive Neural Fuzzy Inference System (ANFIS) Untuk Menguji Kualitas Printed Circuit Board (PCB)

2021 ◽  
Vol 5 (2) ◽  
pp. 79-90
Author(s):  
Tatang Rohana Cucu
Keyword(s):  
Visual Inspection ◽  
Printed Circuit Board ◽  
Fuzzy Inference ◽  
Circuit Board ◽  
Inspection System ◽  
Automated Visual Inspection ◽  
Inference System ◽  
Printed Circuit ◽  
Bahasa Indonesia ◽  
Neural Fuzzy

Pengujian kualitas menggunakan teknik pengolahan citra dan kecerdasan tiruan banyak diterapkan dalam berbagai industri, misalnya industri tekstil, perakitan kendaraan, makanan, minuman, perakitan elektronik, dan lain – lain. Pengujian model ini sering disebut dengan istilah Automated Visual Inspection System (AVIS) atau dalam bahasa Indonesia Sistem Inspeksi Visual Otomatis (SIVO). Penelitian ini mengacu pada model sistem inspeksi, di mana objek pengujiannya adalah keping Printed Circuit Board (PCB). Banyak penelitian tentang pengujian PCB yang sudah dilakukan, tetapi masih banyak yang belum memberikan hasil yang optimum, diantaranya waktu akses yang masih lambat, keakuratan data masih rendah, dan tingkat kesalahan yang masih tinggi. Berdasarkan hasil penelitian dan pengujian yang sudah dilakukan, model ANFIS sangat layak dijadikan sebagai model inferensi kecerdasan buatan dalam sistem yang berbasis inspeksi otomatis khususnya menguji kualitas keping PCB, karena terbukti model ANFIS dengan model hybrid trapesium mf memiliki tingkat kesalahan yang sangat kecil yaitu 4.0186e-007 dan untuk tingkat akurasi pengujian datanya mencapai 99%. 

Size and Defect Detection of Hami Big Jujubes Based on Computer Vision

2012 ◽  
Vol 562-564 ◽  
pp. 750-754 ◽  
Author(s):  
Ben Xue Ma ◽  
Xiang Xiang Qi ◽  
Li Li Wang ◽  
Rong Guang Zhu ◽  
Qin Gang Chen ◽  
...  
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Image Data ◽  
Ccd Camera ◽  
Transverse Diameter ◽  
Testing Time ◽  
Hardware System ◽  
Space Transformation ◽  
Visual Basic6.0 ◽  
Mean And Variance

In order to realize the rapid nondestructive testing for Hami Big Jujubes’ quality detection, a detecting system based on computer vision was established to detect Hami Big Jujubes’ size and defect. The image grabbing card and CCD camera were consisted of the hardware system, which was used to collect image data. Visual Basic6.0 and image processing toolbox of Mil9.0 constituted the software system. The function of MIL9.0 was called in the Visual Basic6.0 to realize the detection. During image processing, the threshold was all chose (0.1,0.7).Many methods were used to identify the features rapidly and get the H value’s mean and variance, such as colour space transformation, mathematical morphology processing and mask etc. Experimental results showed that the correlation coefficient between the projective areas and weights was 0.945.The correlation between projective areas, transverse diameter and vertical diameter was 0.951.The defects grading models were built by BP neural network .The discriminating rate was as high as 99.16％ in training set，and 91.43％ in prediction set. The average testing time was 80 milliseconds, which can satisfy the detection system’s requirements of time．

Study on Parameters Measurement System of Ball-End Cutter Based on Optical Vision Detection

2012 ◽  
Vol 538-541 ◽  
pp. 2109-2112
Author(s):  
Lin Zhi Liu
Keyword(s):  
Visual Inspection ◽  
Detection System ◽  
Ccd Camera ◽  
Optical Microscope ◽  
Least Square ◽  
Inspection System ◽  
Inspection Method ◽  
Optical Microscope Image ◽  
Parameters Measurement ◽  
Vision Detection

In manufacturing field, the geometric parameters measurement of tool is an essential process in manufacturing ball-end cutter. An optical visual inspection system of ball-end cutter parameters was studied through designing CCD camera, optical microscope, image grabbing card, visual light and 3D detection tables. Through the grabbing and processing image information of ball-end cutter, visual inspection method was applied to measure parameters of ball-end cutter. Some algorithms including the gray scale processing, median filtering, edge detection and least square fitting method of measured data were analyzed to develop image processing and tool detection software of ball-end cutter. The reliability and accuracy of this detection system were verified through the practical test.

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