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A Review and Analysis of Automatic Optical Inspection and Quality Monitoring Methods in Electronics Industry
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, micro-electronics, 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.Framework of the IQONIC Project; European Union’s Horizon 2020 Research and Innovation Program
Prevention of Unauthorized Transport of Ore in Opencast Mines Using Automatic Number Plate Recognition
Security in mining is a primary concern, which mainly affects the production cost. An efficiently detecting and deterring theft will maximize the profitability of any mining organization. Many illegal transportation cases were registered in spite of rules imposed by central and state governments under Section 23 (c) of MMDR Act 1957. Use of an automated checkpoint gate based on license plate recognition and biometric fingerprint system for vehicle tracking enhances the security in mines. The method was tested on the number plates with various considerations like clean number plates, clean fingerprints, dusty and faded number plates, dusty fingerprints, and number plates captured by varying distance. By considering all the above conditions the pictures were processed by ANPR and bio-metric fingerprint modules. Vehicle license number plate was captured using a digital camera and the captured RGB image was converted to grayscale image. Thresholding was done to remove unwanted areas from the grayscale image. The characters of the number plate were segmented using Gabor filter. A track-sector matrix was generated by considering the number of pixels in each region and was matched with existing template to identify the character. The fingerprint scans the finger and matches with the template created at the time of fingerprint registration at the machine. The micro-controller accepted the processed output in binary form from ANPR and bio-metric fingerprint system. The micro-controller processed the binary output and the checkpoint gate was closed/open based on the output provided by the microcontroller to motor driver
반도체 제조 공정을 위한 GAN 기반 이종 이미지 정렬 체계
학위논문(석사)--서울대학교 대학원 :공과대학 기계항공공학부,2019. 8. 김도년.In semiconductor manufacturing process, visual inspection on wafer using template-based detection is widely researched topic. As a prerequisite of detection process, new demand for aligning multimodal image has emerged. To address this issue, this paper proposes a framework with GAN based image translation followed by NCC based template matching algorithm. Different from previous function based approaches, our deep learning based framework effectively transforms an image to another domain where template matching is much easier. Also, for practical usage, we propose a new training data generation strategy which allows our model to train from only 20 pre-aligned images. Experimental results on 4 types of manually aligned data, consisted of 400 pairs of images, demonstrate that our method successfully transforms image regardless of the presence of defect or noise. Also, using transformed image, alignment process with NCC based template matching achieved almost 100% accuracy on every types of image. Moreover, our framework shows great efficiency as it takes only 15 minutes for training and 0.25 seconds per image in test time.반도체 공정에서 템플릿을 이용한 비전 기반의 웨이퍼 검사는 널리 연구되는 분야이다. 이러한 검사 과정의 전제 조건으로 멀티모달 이미지 정렬에 대한 새로운 요구가 대두되었다. 이 문제를 해결하기 위해 본 논문은 GAN을 활용한 이미지 변환과 NCC 기반의 템플릿 정렬 알고리즘을 이용한 프레임워크를 제안한다. 이전의 함수 기반 접근법과 달리 딥러닝 기반 프레임워크는 이미지를 템플릿 정렬이 훨씬 용이한 도메인으로 효과적으로 변환한다. 또한 실용적인 관점에서 고안한 새로운 학습 데이터 생성 방법을 통해 오직 20개의 정렬된 초기 데이터를 통해서 딥러닝 모델을 성공적으로 학습할 수 있다. 각각 100쌍의 이미지로 이루어진 4가지 종류의 수작업으로 정렬한 데이터를 사용한 실험 결과를 통해 고안한 방법이 결함이나 노이즈의 존재여부와 상관없이 효과적으로 이미지를 변환한다는 것을 확인할 수 있다. 또한 변환된 이미지를 사용한 NCC 기반의 템플릿 정렬 알고리즘은 이미지 정렬에서 100%에 가까운 정확도를 보인다. 마지막으로 소요 시간에서 프레임워크는 학습에 15분, 테스트 시 이미지당 0.25 초 만을 소모하며 높은 효율을 보인다.1. Introduction 1
2. Proposed Framework 5
2.1 Training image generation and image preprocessing 6
2.2 GAN based image translation and template matching 9
3. Experimental Results 13
3.1 Performance of image generation 14
3.2 Accuracy of template matching 22
3.3 Running time of framework 24
4. Conclusion 26
References 28
Abstract in Korean 31Maste
Investigation of the processes required for the automation of stitchmarking in shoe manufacture
This thesis describes a novel approach to the high speed automatic stitchmarking of shoe upper components by integrating an electrographic printer with a shape recognition system. A critical review of recognition system parameters selects the currently known shape parameters which are most suitable for use in a high speed recognition system with the large number of different shoe components found in a typical shoe factory. These are compared with the parameters actually used in the previously developed recognition system to be used for stitchmarking. A discussion of printing technologies suitable for marking shoe materials with computer generated patterns follows. It is concluded that an electrographic printer has the best combination of characteristics. There follows a description of experiments demonstrating xerography on shoe upper materials, and the design of a system integrating a low-cost laser printer to the recognition system which proved the concept of continuous automatic stitchmarking. With this performing satisfactorily, the system was converted to use a high speed printer requiring the use of an advanced graphics processor for handling the data transformations and interfacing with the printer. Modifications to the printer for operation with shoe materials are described, together with the need for a special toner. A full description of the resulting stitchmarking system is given, followed by details of analyses of its performance. Individual chapters are devoted to the accuracy, recognition efficiency, and the timing of the system. A potential bottleneck in determining the orientation of certain difficult shapes is identified, and faster methods for dealing with these are specially investigated. This concludes that the best approach is to optimise the present method and accelerate the calculations by using a more advanced microprocessor. A discussion of the general running of the machine includes details of problems which occurred with the modified printer mechanism and how these were overcome. Finally, suggestions are made for incorporation in an improved system capable of handling larger shapes with a tenfold speed increase
LHC Days
The main scope of this workshop was to address and discuss a number of key topics relative to the current work in the LHC Division, with the aim of improving our understanding of the main issues and identifying lines of further action. An equally important goal was to bring together project engineers who tend to get increasingly busy and specialised, in order to share views and experience
NASA Tech Briefs Index, 1978
Approximately 601 announcements of new technology derived from the research and development activities of the National Aeronautics and Space Administration are presented. Emphasis is placed on information considered likely to be transferrable across industrial, regional, or disciplinary lines. Subject matter covered includes: electronic components and circuits; electron systems; physical sciences; materials; life sciences; mechanics; machinery; fabrication technology; and mathematics and information sciences
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