Defect detection of IC wafer based on two-dimension wavelet transform

Liu, Hongxia; Zhou, Wen; Kuang, Qianwei; Cao, Lei; Gao, Bo

doi:10.1016/j.mejo.2010.01.015

Cited by 22 publications

(4 citation statements)

References 15 publications

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“…Moreover, the proposed approach can detect subtle defects as small as 1-pixel wide. Liu et al in [114], [115] proposed similar approach to detect IC wafer defects. In their studies they used 2D and 1D DWT respectively to extract a standard template image form three defected images using comparison and subtraction approaches.…”

Section: D: Hough Transformmentioning

confidence: 99%

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: D: Hough Transformmentioning

confidence: 99%

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

2020

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“…In general, the detection is based on reference image or no referential approaches. Morphological processing [23,24] and neural network [25] are without references, while methods [26,27] need the standard image. Finally, image registration based on the SURF algorithm is another way to align the detected image and the standard image.…”

Section: Introductionmentioning

confidence: 99%

Image Wafer Inspection based on Template Matching

Barone¹

2020

Computer Science &Amp; Information Technology (CS &Amp; IT)

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This paper presents a template matching technique for detecting defects in VLSI wafer images. This method is based on traditional techniques of image analysis and image registration, but it combines the prior art of image wafer inspection in a new way, using prior knowledge like the design layout of VLSI wafer manufacturing process. This technique requires a golden template of the patterned wafer image under inspection which is obtained from the wafer image itself mixed to the layout design schemes. First a mapping between physical space and pixel space is needed. Then a template matching is applied for a more accurate alignment between wafer device and template. Finally, a segmented comparison is used for finding out possible defects. Results of the proposed method are presented in terms of visual quality of defect detection, any misalignment at topology level and number of correctly detected defective devices.

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“…There are many papers written on noncontact-based method for defect inspection but none applied to WBs. Most of these papers are on inspection of fabric, textile, weld, etc [9]~ [17] . In Gang Wang [9] , used the subtraction background method for welding defect detection.…”

Section: Introductionmentioning

confidence: 99%

“…The approach is quite simple and efficient; however, the requirement for reference image still remains. In comparison, Hongxia Liu et.al [17] used 2-D Wavelet Transform (2-D DWT) approach, in which template images are not necessary for defect detection of IC wafer. The method extracts the standard image, no defect, by applying 2-D DWT for three different IC images with the same layout.…”

Section: Introductionmentioning

confidence: 99%

Damage Inspection of Wiper Blades Using Image Processing Techniques

Nguyen

Nguyễn

Nguyen

2011

AEJ

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The working part of Wiper Blades (WBs), made from PU material, are more vulnerable to contactbased solutions than other methods. In conventional approaches, sharp styluses employed as probes for tracking damaged edges are usually forced to wear out after a long time of the scanning process, thereby producing unreliable results. As a result, a machine vision-based system is proposed in this paper for WB damage inspection. Double threshold and morphological operations are used for defect verification. Defects are then derived using the background subtraction method before applying region-based algorithm for assessment. Results of experiments have demonstrated the reliability and flexibility of the new approach. Differences between the novel approach and the conventional method, which uses piezoelectric sensor, are also presented in this paper.

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Defect detection of IC wafer based on two-dimension wavelet transform

Cited by 22 publications

References 15 publications

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

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

Image Wafer Inspection based on Template Matching

Damage Inspection of Wiper Blades Using Image Processing Techniques

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