• Title/Summary/Keyword: Modified illumination

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Modified Illumination by Binary Phase Diffractive Patterns on the Backside of a Photomask (마스크 뒷면에 2 위상 회절 격자를 구현한 변형 조명 방법)

  • 이재철;오용호;고춘수
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
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    • v.17 no.7
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    • pp.697-700
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    • 2004
  • We propose a method that realizes the modified illumination by implementing a binary phase grating at the backside of a photomask. By modeling the relationship between the shape of a grating on the photomask and the light intensity at the pupil plane, we developed a program named MIDAS that finds the optimum grating pattern with a stochastic approach. After applying the program to several examples, we found that the program finds the grating pattern for the modified illumination that we want. By applying the grating at the backside of a photomask, the light efficiency of modified illumination may be improved.

Modified Illumination with a Concentric Circular Grating at the Backside of a Photomask (마스크 뒷면에 동심원 격자를 사용한 변형조명 방법)

  • Oh, Yong-Ho;Go, Chun-Soo;Lim, Sungwoo;Lee, Jai-Cheol
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
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    • v.18 no.3
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    • pp.212-215
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    • 2005
  • Modified illumination techniques have been used to enhance the resolution of the sub-wavelength lithography. But, since they shield the central part of incident light, the light efficiency is seriously degraded, which in turn reduces the throughput of a lithography process. In this research, we introduced an annular illumination structure that enhances the light efficiency with a concentric circular grating at the backside of a photomask. The efficiency of the structure was theoretically analyzed.

Design and implementation of optical identification system using visible light and infrared

  • Lee, Seong-Ho
    • Journal of Sensor Science and Technology
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    • v.30 no.4
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    • pp.196-203
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    • 2021
  • In this study, an optical identification system was developed, wherein visible light is used to transmit the interrogating signal, and infrared is used to send the response signal. In the reader, visible light from a light emitting diode (LED) array was modulated via modified pulse width modulation for flicker-free illumination and dimming control. Moreover, the duty factor of the dimming control time was employed to control the illumination from the LED. In the transponder, the spike signal in the output of the high-pass filter was utilized to recover the interrogating signal while preventing interference from the 120-Hz noise from adjacent lighting lamps. The illumination was controlled in 26-86% range of the constant wave LED illumination by changing the duty factor from 20% to 90%. This configuration is advantageous for the construction of optical identification systems for automatic security check and car fare calculation at toll gates or parking facilities.

An Illumination Invariant Traffic Sign Recognition in the Driving Environment for Intelligence Vehicles (지능형 자동차를 위한 조명 변화에 강인한 도로표지판 검출 및 인식)

  • Lee, Taewoo;Lim, Kwangyong;Bae, Guntae;Byun, Hyeran;Choi, Yeongwoo
    • Journal of KIISE
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    • v.42 no.2
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    • pp.203-212
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    • 2015
  • This paper proposes a traffic sign recognition method in real road environments. The video stream in driving environments has two different characteristics compared to a general object video stream. First, the number of traffic sign types is limited and their shapes are mostly simple. Second, the camera cannot take clear pictures in the road scenes since there are many illumination changes and weather conditions are continuously changing. In this paper, we improve a modified census transform(MCT) to extract features effectively from the road scenes that have many illumination changes. The extracted features are collected by histograms and are transformed by the dense descriptors into very high dimensional vectors. Then, the high dimensional descriptors are encoded into a low dimensional feature vector by Fisher-vector coding and Gaussian Mixture Model. The proposed method shows illumination invariant detection and recognition, and the performance is sufficient to detect and recognize traffic signs in real-time with high accuracy.

Illumination Invariant Face Tracking on Smart Phones using Skin Locus based CAMSHIFT

  • Bui, Hoang Nam;Kim, SooHyung;Na, In Seop
    • Smart Media Journal
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    • v.2 no.4
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    • pp.9-19
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    • 2013
  • This paper gives a review on three illumination issues of face tracking on smart phones: dark scenes, sudden lighting change and backlit effect. First, we propose a fast and robust face tracking method utilizing continuous adaptive mean shift algorithm (CAMSHIFT) and CbCr skin locus. Initially, the skin locus obtained from training video data. After that, a modified CAMSHIFT version based on the skin locus is accordingly provided. Second, we suggest an enhancement method to increase the chance of detecting faces, an important initialization step for face tracking, under dark illumination. The proposed method works comparably with traditional CAMSHIFT or particle filter, and outperforms these methods when dealing with our public video data with the three illumination issues mentioned above.

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Distributed Video Coding for Illumination Compensation of Multi-view Video

  • Park, Sean-Ae;Sim, Dong-Gyu;Jeon, Byeung-Woo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.4 no.6
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    • pp.1222-1236
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    • 2010
  • In this paper, we propose an improved distributed multi-view video coding method that is robust to illumination changes among different views. The use of view dependency is not effective for multi-view video because each view has different intrinsic and extrinsic camera parameters. In this paper, a modified distributed multi-view coding method is presented that applies illumination compensation when generating side information. The proposed encoder codes DC values of discrete cosine transform (DCT) coefficients separately by entropy coding. The proposed decoder can generate more accurate side information by using the transmitted DC coefficients to compensate for illumination changes. Furthermore, AC coefficients are coded with conventional entropy or channel coders depending on the frequency band. We found that the proposed algorithm is about 0.1~0.5 dB better than conventional algorithms.

Color Image Rendering using A Modified Image Formation Model (변형된 영상 생성 모델을 이용한 칼라 영상 보정)

  • Choi, Ho-Hyoung;Yun, Byoung-Ju
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.1
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    • pp.71-79
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    • 2011
  • The objective of the imaging pipeline is to transform the original scene into a display image that appear similar, Generally, gamma adjustment or histogram-based method is modified to improve the contrast and detail. However, this is insufficient as the intensity and the chromaticity of illumination vary with geometric position. Thus, MSR (Multi-Scale Retinex) has been proposed. the MSR is based on a channel-independent logarithm, and it is dependent on the scale of the Gaussian filter, which varies according to input image. Therefore, after correcting the color, image quality degradations, such as halo, graying-out, and dominated color, may occur. Accordingly, this paper presents a novel color correction method using a modified image formation model in which the image is divided into three components such as global illumination, local illumination, and reflectance. The global illumination is obtained through Gaussian filtering of the original image, and the local illumination is estimated by using JND-based adaptive filter. Thereafter, the reflectance is estimated by dividing the original image by the estimated global and the local illumination to remove the influence of the illumination effects. The output image is obtained based on sRGB color representation. The experiment results show that the proposed method yields better performance of color correction over the conventional methods.

Face Recognition using Modified Local Directional Pattern Image (Modified Local Directional Pattern 영상을 이용한 얼굴인식)

  • Kim, Dong-Ju;Lee, Sang-Heon;Sohn, Myoung-Kyu
    • KIPS Transactions on Software and Data Engineering
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    • v.2 no.3
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    • pp.205-208
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    • 2013
  • Generally, binary pattern transforms have been used in the field of the face recognition and facial expression, since they are robust to illumination. Thus, this paper proposes an illumination-robust face recognition system combining an MLDP, which improves the texture component of the LDP, and a 2D-PCA algorithm. Unlike that binary pattern transforms such as LBP and LDP were used to extract histogram features, the proposed method directly uses the MLDP image for feature extraction by 2D-PCA. The performance evaluation of proposed method was carried out using various algorithms such as PCA, 2D-PCA and Gabor wavelets-based LBP on Yale B and CMU-PIE databases which were constructed under varying lighting condition. From the experimental results, we confirmed that the proposed method showed the best recognition accuracy.

Robust Color Classifier for Robot Soccer System under Illumination Variations (조명 변화에 강인한 로봇 축구 시스템의 색상 분류기)

  • 이성훈;박진현;전향식;최영규
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.53 no.1
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    • pp.32-39
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    • 2004
  • The color-based vision systems have been used to recognize our team robots, the opponent team robots and a ball in the robot soccer system. The color-based vision systems have the difficulty in that they are very sensitive to color variations brought by brightness changes. In this paper, a neural network trained with data obtained from various illumination conditions is used to classify colors in the modified YUV color space for the robot soccer vision system. For this, a new method to measure brightness is proposed by use of a color card. After the neural network is constructed, a look-up-table is generated to replace the neural network in order to reduce the computation time. Experimental results show that the proposed color classification method is robust under illumination variations.

Visual Observation Confidence based GMM Face Recognition robust to Illumination Impact in a Real-world Database

  • TRA, Anh Tuan;KIM, Jin Young;CHAUDHRY, Asmatullah;PHAM, The Bao;Kim, Hyoung-Gook
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.4
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    • pp.1824-1845
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    • 2016
  • The GMM is a conventional approach which has been recently applied in many face recognition studies. However, the question about how to deal with illumination changes while ensuring high performance is still a challenge, especially with real-world databases. In this paper, we propose a Visual Observation Confidence (VOC) measure for robust face recognition for illumination changes. Our VOC value is a combined confidence value of three measurements: Flatness Measure (FM), Centrality Measure (CM), and Illumination Normality Measure (IM). While FM measures the discrimination ability of one face, IM represents the degree of illumination impact on that face. In addition, we introduce CM as a centrality measure to help FM to reduce some of the errors from unnecessary areas such as the hair, neck or background. The VOC then accompanies the feature vectors in the EM process to estimate the optimal models by modified-GMM training. In the experiments, we introduce a real-world database, called KoFace, besides applying some public databases such as the Yale and the ORL database. The KoFace database is composed of 106 face subjects under diverse illumination effects including shadows and highlights. The results show that our proposed approach gives a higher Face Recognition Rate (FRR) than the GMM baseline for indoor and outdoor datasets in the real-world KoFace database (94% and 85%, respectively) and in ORL, Yale databases (97% and 100% respectively).