• Title/Summary/Keyword: Bad pixel

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Performance Improvement of Stereo Matching by Image Segmentation based on Color and Multi-threshold (컬러와 다중 임계값 기반 영상 분할 기법을 통한 스테레오 매칭의 성능 향상)

  • Kim, Eun Kyeong;Cho, Hyunhak;Jang, Eunseok;Kim, Sungshin
    • Journal of the Korean Institute of Intelligent Systems
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    • v.26 no.1
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    • pp.44-49
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    • 2016
  • This paper proposed the method to improve performance of a pixel, which has low accuracy, by applying image segmentation methods based on color and multi-threshold of brightness. Stereo matching is the process to find the corresponding point on the right image with the point on the left image. For this process, distance(depth) information in stereo images is calculated. However, in the case of a region which has textureless, stereo matching has low accuracy and bad pixels occur on the disparity map. In the proposed method, the relationship between adjacent pixels is considered for compensating bad pixels. Generally, the object has similar color and brightness. Therefore, by considering the relationship between regions based on segmented regions by means of color and multi-threshold of brightness respectively, the region which is considered as parts of same object is re-segmented. According to relationship information of segmented sets of pixels, bad pixels in the disparity map are compensated efficiently. By applying the proposed method, the results show a decrease of nearly 28% in the number of bad pixels of the image applied the method which is established.

A Study of Edge Detection for Auto Focus of Infrared Camera

  • Park, Hee-Duk
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.1
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    • pp.25-32
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    • 2018
  • In this paper, we propose an edge detection algorithm for auto focus of infrared camera. We designed and implemented the edge detection of infrared image by using a spatial filter on FPGA. The infrared camera should be designed to minimize the image processing time and usage of hardware resource because these days surveillance systems should have the fast response and be low size, weight and power. we applied the $3{\times}3$ mask filter which has an advantage of minimizing the usage of memory and the propagation delay to process filtering. When we applied Laplacian filter to extract contour data from an image, not only edge components but also noise components of the image were extracted by the filter. These noise components make it difficult to determine the focus state. Also a bad pixel of infrared detector causes a problem in detecting the edge components. So we propose an adaptive edge detection filter that is a method to extract only edge components except noise components of an image by analyzing a variance of pixel data in $3{\times}3$ memory area. And we can detect the bad pixel and replace it with neighboring normal pixel value when we store a pixel in $3{\times}3$ memory area for filtering calculation. The experimental result proves that the proposed method is effective to implement the edge detection for auto focus in infrared camera.

Detecting Digital Micromirror Device Malfunctions in High-throughput Maskless Lithography

  • Kang, Minwook;Kang, Dong Won;Hahn, Jae W.
    • Journal of the Optical Society of Korea
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    • v.17 no.6
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    • pp.513-517
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    • 2013
  • Recently, maskless lithography (ML) systems have become popular in digital manufacturing technologies. To achieve high-throughput manufacturing processes, digital micromirror devices (DMD) in ML systems must be driven to their operational limits, often in harsh conditions. We propose an instrument and algorithm to detect DMD malfunctions to ensure perfect mask image transfer to the photoresist in ML systems. DMD malfunctions are caused by either bad DMD pixels or data transfer errors. We detect bad DMD pixels with $20{\times}20$ pixel by white and black image tests. To analyze data transfer errors at high frame rates, we monitor changes in the frame rate of a target DMD pixel driven by the input data with a set frame rate of up to 28000 frames per second (fps). For our data transfer error detection method, we verified that there are no data transfer errors in the test by confirming the agreement between the input frame rate and the output frame rate within the measurement accuracy of 1 fps.

MicroLED Transfer, Bonding, and Bad Pixel Repair Technology (마이크로 LED 전사, 접합, 그리고 불량 화소 수리 기술)

  • Choi, K.S.;Eom, Y.S.;Moon, S.H.;Yun, H.G.;Joo, J.;Choi, G.M.
    • Electronics and Telecommunications Trends
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    • v.37 no.2
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    • pp.53-61
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    • 2022
  • MicroLEDs have various advantages and application areas and are in the spotlight as next-generation displays. Nevertheless, the commercialization of microLEDs is slow because of high cost as well as difficulties in the transfer, bonding, and bad pixel repairing process. In this study, we review the development trends of transfer, bonding, and defective pixel repair technologies, which are critical for microLED commercialization, focusing on materials that determine these technologies. In addition, we focus on the simultaneous transfer bonding technology developed by the Electronics and Telecommunications Research Institute, which has been attracting enormous research attention recently.

Depth Up-Sampling via Pixel-Classifying and Joint Bilateral Filtering

  • Ren, Yannan;Liu, Ju;Yuan, Hui;Xiao, Yifan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.7
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    • pp.3217-3238
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    • 2018
  • In this paper, a depth image up-sampling method is put forward by using pixel classifying and jointed bilateral filtering. By analyzing the edge maps originated from the high-resolution color image and low-resolution depth map respectively, pixels in up-sampled depth maps can be classified into four categories: edge points, edge-neighbor points, texture points and smooth points. First, joint bilateral up-sampling (JBU) method is used to generate an initial up-sampling depth image. Then, for each pixel category, different refinement methods are employed to modify the initial up-sampling depth image. Experimental results show that the proposed algorithm can reduce the blurring artifact with lower bad pixel rate (BPR).

An Efficient Dead Pixel Detection Algorithm and VLSI Implementation (효율적인 불량화소 검출 알고리듬 및 하드웨어 구현)

  • An Jee-Hoon;Lee Won-Jae;Kim Jae-Seok
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.43 no.9 s.351
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    • pp.38-43
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    • 2006
  • In this paper, we propose the efficient dead pixel detection algorithm for CMOS image sensors and its hardware architecture. The CMOS image sensors as image input devices are becoming popular due to the demand for miniaturized, low-power and cost-effective imaging systems. However, the presence of the dead pixels degrade the image quality. To detect the dead pixels, the proposed algorithm is composed of scan, trace and detection step. The experimental results showed that it could detect 99.99% of dead pixels. It was designed in a hardware description language and total logic gate count is 3.2k using 0.25 CMOS standard cell library.

일반적 총 변이와 가이드 깊이맵을 이용한 스테레오 정합

  • ;Ho, Yo-Seong
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2016.11a
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    • pp.96-97
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    • 2016
  • 스테레오 정합은 컴퓨터 비전 분야에서 활발하게 연구되고 있는 연구 주제로 서로 다른 위치에서 획득된 두 영상을 정합하여 거리 정보를 얻는 방법이다. 이 방법은 초음파나 레이저를 광원으로 거리를 측정하는 것보다 실제 응용 환경의 제약을 적게 받아 다양한 분야에서 응용되고 있다. 하지만, 텍스쳐가 반복되거나 텍스쳐가 없는 영역 혹은 객체의 경계 부근에서 정확한 깊이 정보를 획득하지 못한다는 단점이 있다. 본 논문은 일반적 총 변이와 가이드 깊이맵을 사용하여 정합 비용을 정제 방법을 사용하여 정확한 깊이 정보 획득 방법을 제안한다. 실험 결과를 통해 제안한 방법이 기존의 색상 영상의 텍스쳐 복사 문제를 해결하였으며, 기존의 방법에 비해 bad pixel rates 측면에서 월등한 성능을 보이는 것을 확인하였다.

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Adaptive Reconstruction of Harmonic Time Series Using Point-Jacobian Iteration MAP Estimation and Dynamic Compositing: Simulation Study

  • Lee, Sang-Hoon
    • Korean Journal of Remote Sensing
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    • v.24 no.1
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    • pp.79-89
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    • 2008
  • Irregular temporal sampling is a common feature of geophysical and biological time series in remote sensing. This study proposes an on-line system for reconstructing observation image series contaminated by noises resulted from mechanical problems or sensing environmental condition. There is also a high likelihood that during the data acquisition periods the target site corresponding to any given pixel may be covered by fog or cloud, thereby resulting in bad or missing observation. The surface parameters associated with the land are usually dependent on the climate, and many physical processes that are displayed in the image sensed from the land then exhibit temporal variation with seasonal periodicity. A feedback system proposed in this study reconstructs a sequence of images remotely sensed from the land surface having the physical processes with seasonal periodicity. The harmonic model is used to track seasonal variation through time, and a Gibbs random field (GRF) is used to represent the spatial dependency of digital image processes. The experimental results of this simulation study show the potentiality of the proposed system to reconstruct the image series observed by imperfect sensing technology from the environment which are frequently influenced by bad weather. This study provides fundamental information on the elements of the proposed system for right usage in application.

An Efficient Dead Pixel Detection Algorithm Implementation for CMOS Image Sensor (CMOS 이미지 센서에서의 효율적인 불량화소 검출을 위한 알고리듬 및 하드웨어 설계)

  • An, Jee-Hoon;Shin, Seung-Gi;Lee, Won-Jae;Kim, Jae-Seok
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.44 no.4
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    • pp.55-62
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    • 2007
  • This paper proposes a defective pixel detection algorithm and its hardware structure for CCD/CMOS image sensor. In previous algorithms, the characteristics of image have not been considered. Also, some algorithms need quite a time to detect defective pixels. In order to make up for those disadvantages, the proposed defective pixel detection method detects defective pixels efficiently by considering the edges in the image and verifies them using several frames while checking scene-changes. Whenever scene-change is occurred, potentially defective pixels are checked and confirmed whether it is defective or not. Test results showed that the correct detection rate in a frame was increased 6% and the defective pixel verification time was decreased 60%. The proposed algorithm was implemented with verilog HDL. The edge indicator in color interpolation block was reused. Total logic gate count was 5.4k using 0.25um CMOS standard cell library.

Face and Hand Tracking using MAWUPC algorithm in Complex background (복잡한 배경에서 MAWUPC 알고리즘을 이용한 얼굴과 손의 추적)

  • Lee, Sang-Hwan;An, Sang-Cheol;Kim, Hyeong-Gon;Kim, Jae-Hui
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.39 no.2
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    • pp.39-49
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    • 2002
  • This paper proposes the MAWUPC (Motion Adaptive Weighted Unmatched Pixel Count) algorithm to track multiple objects of similar color The MAWUPC algorithm has the new method that combines color and motion effectively. We apply the MAWUPC algorithm to face and hand tracking against complex background in an image sequence captured by using single camera. The MAWUPC algorithm is an improvement of previously proposed AWUPC (Adaptive weighted Unmatched Pixel Count) algorithm based on the concept of the Moving Color that combines effectively color and motion information. The proposed algorithm incorporates a color transform for enhancing a specific color, the UPC(Unmatched Pixel Count) operation for detecting motion, and the discrete Kalman filter for reflecting motion. The proposed algorithm has advantages in reducing the bad effect of occlusion among target objects and, at the same time, in rejecting static background objects that have a similar color to tracking objects's color. This paper shows the efficiency of the proposed MAWUPC algorithm by face and hands tracking experiments for several image sequences that have complex backgrounds, face-hand occlusion, and hands crossing.