• 제목/요약/키워드: semiconductor image

검색결과 462건 처리시간 0.053초

Image Processing and Deep Learning-based Defect Detection Theory for Sapphire Epi-Wafer in Green LED Manufacturing

  • Suk Ju Ko;Ji Woo Kim;Ji Su Woo;Sang Jeen Hong;Garam Kim
    • 반도체디스플레이기술학회지
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    • 제22권2호
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    • pp.81-86
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    • 2023
  • Recently, there has been an increased demand for light-emitting diode (LED) due to the growing emphasis on environmental protection. However, the use of GaN-based sapphire in LED manufacturing leads to the generation of defects, such as dislocations caused by lattice mismatch, which ultimately reduces the luminous efficiency of LEDs. Moreover, most inspections for LED semiconductors focus on evaluating the luminous efficiency after packaging. To address these challenges, this paper aims to detect defects at the wafer stage, which could potentially improve the manufacturing process and reduce costs. To achieve this, image processing and deep learning-based defect detection techniques for Sapphire Epi-Wafer used in Green LED manufacturing were developed and compared. Through performance evaluation of each algorithm, it was found that the deep learning approach outperformed the image processing approach in terms of detection accuracy and efficiency.

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CMOS Image sensor 를 위한 효과적인 플리커 검출기 설계 (Design of Efficient Flicker Detector for CMOS Image Sensor)

  • 이평우;이정국;김채성
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2005년도 추계종합학술대회
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    • pp.739-742
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    • 2005
  • In this paper, an efficient detection algorithm for the flicker, which is caused by mismatching between light frequency and exposure time at CMOS image sensor (CIS), is proposed. The flicker detection can be implemented by specific hardware or complex signal processing logic. However it is difficult to implement on single chip image sensor, which has pixel, CDS, ADC, and ISP on a die, because of limited die area. Thus for the flicker detection, the simple algorithm and high accuracy should be achieved on single chip image sensor,. To satisfy these purposes, the proposed algorithm organizes only simple operation, which calculates the subtraction of horizontal luminance mean between continuous two frames. This algorithm was verified with MATLAB and Xilinx FPGA, and it is implemented with Magnachip 0.18 standard cell library. As a result, the accuracy is 95% in average on FPGA emulation and the consumed gate count is about 7,500 gates (@40MHz) for implementation using Magnachip 0.18 process.

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이미지 검색을 위한 칼라 분포 기술자의 성능 평가 (An Empirical Evaluation of Color Distribution Descriptor for Image Search)

  • 이춘상;이요환;김영섭;이상범
    • 반도체디스플레이기술학회지
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    • 제5권2호
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    • pp.27-31
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    • 2006
  • As more and more digital images are made by various applications, image retrieval becomes a primary concern in technology of multimedia. This paper presents color based descriptor that uses information of color distribution in color images which is the most basic element for image search and performance of proposed visual feature is evaluated through the simulation. In designing the image search descriptor used color histogram, HSV, Daubechies 9/7 and 2 level wavelet decomposition provide better results than other parameters in terms of computational time and performances. Also histogram quadratic matrix outperforms the sum of absolute difference in similarity measurements, but spends more than 60 computational times.

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지리적 위치 정보를 이용한 사진 영상 검색 (Photo Image Retrieval using Geo-location Information)

  • 이용환;김영섭
    • 반도체디스플레이기술학회지
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    • 제7권4호
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    • pp.57-62
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    • 2008
  • Image retrieval is one of the most exciting and rapidly growing research issues in the field of multimedia technology. This paper proposes a new method that performs search the relevant images by using query-by-example. The proposed method for search and retrieval of images utilizes the location information where the image had been taken. The system associates the photo images with their corresponding GPS coordinates that are used as metadata for searching. Experimental results show that the proposed method demonstrates better performance improving up to 59% of average recall and 49% of average precision. Moreover, we learned from the experimental results geo-location information embedded within the image header is more effective and positive on the search and storage.

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영상 이진화와 템플릿 매칭을 이용한 자동차 번호판 인식 시스템 (Vehicle License Plate Recognition System Using Image Binarization and Template Matching)

  • 오수진;박천수
    • 반도체디스플레이기술학회지
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    • 제13권2호
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    • pp.7-12
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    • 2014
  • A vehicle license plate includes the most important information for recognition and classification of the vehicle. In this paper, we propose a vehicle license plate recognition system using image binarization and template matching. In the proposed system, an image of the vehicle license plate is converted into a gray scale image and the gray image undergoes the binarization process. Finally, the numbers on the plate are extracted from the binary image using the template matching algorithm.

병렬처리 기반 정지영상 인식자 생성 (Parallel Processing based Image Identifier Generation)

  • 고미은;박제호;박용범;서원택
    • 반도체디스플레이기술학회지
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    • 제16권1호
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    • pp.6-10
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    • 2017
  • Recent enhancement in the still image acquisition devices has been widely perpetrated into the daily life of the common people. Due to this trend, the voluminous still images, that are produced and shared in the personal or the massive storage, need to controlled with effective and efficient management. The human-devised or system-generated still image identifiers used for the identification of the images are at risk in the situation of unexpected changing or eliminating of the identifiers. In this paper, we propose a parallel processing based method for still image identifier generation by utilizing the still image internal features.

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연결 성분 분류를 이용한 PCB 결함 검출 (PCB Defects Detection using Connected Component Classification)

  • 정민철
    • 반도체디스플레이기술학회지
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    • 제10권1호
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    • pp.113-118
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    • 2011
  • This paper proposes computer visual inspection algorithms for PCB defects which are found in a manufacturing process. The proposed method can detect open circuit and short circuit on bare PCB without using any reference images. It performs adaptive threshold processing for the ROI (Region of Interest) of a target image, median filtering to remove noises, and then analyzes connected components of the binary image. In this paper, the connected components of circuit pattern are defined as 6 types. The proposed method classifies the connected components of the target image into 6 types, and determines an unclassified component as a defect of the circuit. The analysis of the original target image detects open circuits, while the analysis of the complement image finds short circuits. The machine vision inspection system is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiment results show that the proposed algorithms are quite successful.

SIFT 와 SURF 알고리즘의 성능적 비교 분석 (Comparative Analysis of the Performance of SIFT and SURF)

  • 이용환;박제호;김영섭
    • 반도체디스플레이기술학회지
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    • 제12권3호
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    • pp.59-64
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    • 2013
  • Accurate and robust image registration is important task in many applications such as image retrieval and computer vision. To perform the image registration, essential required steps are needed in the process: feature detection, extraction, matching, and reconstruction of image. In the process of these function, feature extraction not only plays a key role, but also have a big effect on its performance. There are two representative algorithms for extracting image features, which are scale invariant feature transform (SIFT) and speeded up robust feature (SURF). In this paper, we present and evaluate two methods, focusing on comparative analysis of the performance. Experiments for accurate and robust feature detection are shown on various environments such like scale changes, rotation and affine transformation. Experimental trials revealed that SURF algorithm exhibited a significant result in both extracting feature points and matching time, compared to SIFT method.

딥-러닝을 활용한 안드로이드 플랫폼에서의 이미지 시맨틱 분할 구현 (Implementation of Image Semantic Segmentation on Android Device using Deep Learning)

  • 이용환;김영섭
    • 반도체디스플레이기술학회지
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    • 제19권2호
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    • pp.88-91
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    • 2020
  • Image segmentation is the task of partitioning an image into multiple sets of pixels based on some characteristics. The objective is to simplify the image into a representation that is more meaningful and easier to analyze. In this paper, we apply deep-learning to pre-train the learning model, and implement an algorithm that performs image segmentation in real time by extracting frames for the stream input from the Android device. Based on the open source of DeepLab-v3+ implemented in Tensorflow, some convolution filters are modified to improve real-time operation on the Android platform.

하나의 웨이퍼 전체 영상을 이용한 웨이퍼 Pre-Alignment 시스템 (A Wafer Pre-Alignment System Using One Image of a Whole Wafer)

  • 구자명;조태훈
    • 반도체디스플레이기술학회지
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    • 제9권3호
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    • pp.47-51
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    • 2010
  • This paper presents a wafer pre-alignment system which is improved using the image of the entire wafer area. In the previous method, image acquisition for wafer takes about 80% of total pre-alignment time. The proposed system uses only one image of entire wafer area via a high-resolution CMOS camera, and so image acquisition accounts for nearly 1% of total process time. The larger FOV(field of view) to use the image of the entire wafer area worsen camera lens distortion. A camera calibration using high order polynomials is used for accurate lens distortion correction. And template matching is used to find a correct notch's position. The performance of the proposed system was demonstrated by experiments of wafer center alignment and notch alignment.