IC Solder Joint Inspection Based on an Adaptive-Template Method

Ye, Qian; Cai, Nian; Li, Jiaming; Li, Feiyang; Wang, Han; Chen, Xindu

doi:10.1109/tcpmt.2018.2812815

Cited by 22 publications

(21 citation statements)

References 14 publications

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“…Since the existence of the father of all displays, the cathode ray tube, electronics displays became an important aspect of human's modern life [210]. Currently, Liquid Crystal Display (LCDs) are the dominant technologies in the field of Missing Solder [139], [158]- [163] Insufficient or open solder [143], [158]- [172] Excess or bridged solder [139], [143], [148], [158]- [170] Pseudo Solder (cold solder) [139], [159], [160], [163], [171], [172] Solder Joint Overall Quality [173]- [176] Solder Paste Inspection [142], [177], [178] Electronic…”

Section: Fpd Defectsmentioning

confidence: 99%

“…To reduce false alarm rates, the carrier of the inspected plates were coated with high reflective substance so that the subject appears darker. Three-layer tiered light [139], [159], [160], [163], [164], [171]- [176], [182], [305], [306], [308] This setup was used for solder joints inspection in PCBs. The setup consisted of 3 (red, green and blue) circular ringshaped lamps at 3levels constructed on hemispherical way with different light reflection angles that can be fixed or controlled by host computer.…”

Section: A Contrast and Illumination Settingsmentioning

confidence: 99%

“…However, the number of samples used for testing and the fact that no classification algorithm was considered are major drawbacks in the study. Ye et al in [176] inspected the IC solder joint component based on an algorithm they call it "Adaptive template method". The algorithm start working by a constructing a dictionary of qualified IC solder images.…”

Section: D: Hough Transformmentioning

confidence: 99%

“…Despite of the low false alarm rate achieved in this study; the overall accuracy is relatively low compared with other studies. In Ye et al [176], after using the adaptive template method, they used a conditional statement using a threshold to identify whether a pixel in the difference image is a potential solder joint defect pixel or not. The threshold R is defined based on the hue channel difference between the template and sample image from the dictionary.…”

Section: ) Rule-based Classificationmentioning

confidence: 99%

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A Review and Analysis of Automatic Optical Inspection and Quality Monitoring Methods in Electronics Industry

2020

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Electronics industry is one of the fastest evolving, innovative, and most competitive industries. In order to meet the high consumption demands on electronics components, quality standards of the products must be well-maintained. Automatic optical inspection (AOI) is one of the non-destructive techniques used in quality inspection of various products. This technique is considered robust and can replace human inspectors who are subjected to dull and fatigue in performing inspection tasks. A fully automated optical inspection system consists of hardware and software setups. Hardware setup include image sensor and illumination settings and is responsible to acquire the digital image, while the software part implements an inspection algorithm to extract the features of the acquired images and classify them into defected and non-defected based on the user requirements. A sorting mechanism can be used to separate the defective products from the good ones. This article provides a comprehensive review of the various AOI systems used in electronics, microelectronics , and opto-electronics industries. In this review the defects of the commonly inspected electronic components, such as semiconductor wafers, flat panel displays, printed circuit boards and light emitting diodes, are first explained. Hardware setups used in acquiring images are then discussed in terms of the camera and lighting source selection and configuration. The inspection algorithms used for detecting the defects in the electronic components are discussed in terms of the preprocessing, feature extraction and classification tools used for this purpose. Recent articles that used deep learning algorithms are also reviewed. The article concludes by highlighting the current trends and possible future research directions.

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Section: Fpd Defectsmentioning

confidence: 99%

Section: A Contrast and Illumination Settingsmentioning

confidence: 99%

Section: D: Hough Transformmentioning

confidence: 99%

Section: ) Rule-based Classificationmentioning

confidence: 99%

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A Review and Analysis of Automatic Optical Inspection and Quality Monitoring Methods in Electronics Industry

2020

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“…To improve the inspection rate of solder joint defects (such as pseudo-solder, insufficient solder), image compression, image segmentation [26], image enhancement and image filtering, etc. are used in automatic optical inspection (AOI) [1], [31]. Compressive Sensing (CS) is a sampling paradigm that provides signal compression at a significantly lower rate than the Nyquist rate [9], [10].…”

Section: Introductionmentioning

confidence: 99%