• 제어로봇시스템학회논문지
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• 제17권5호
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• pp.479-483
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• 2011

The automation of production process is actively expanding for the purpose of the cost reduction and quality assurance. Among these, automatic tracking of the product along the whole process of the production is also important topic. Typically this is done by adopting OCR technology. Conventional OCR technology operates well on the rather good quality of the image like as printed characters on the paper. In industrial application, IDs are marked on the metal surface, and this cause the height difference between background material and character. Illumination systems that guarantee an image with good quality may be a solution, but it is rather difficult to design such an illumination system. This paper proposes an algorithm for the recognition of vehicle's ID characters using edge projection and PCA (Principal Component Analysis). Proposed algorithm robustly operates under illumination change using the same parameters. Experimental results show the feasibility of the proposed algorithm.

• 한국가구학회지
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• 제24권1호
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• pp.33-41
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• 2013

As professional postnatal care systems have been rapidly supplied, there is sharp increase of postnatal care centers without legal regulations for a mother and a infant. For the quick recovery of mothers, newborn infants that have weaker immune systems are being managed in group in the postnatal care centers. Recently, the attention of the postnatal care centers has been growing because the problem of pneumonia which led to result in a casuality in a infant unit was happen. So, this research analyzed the indoor environment of infant unit through measuring formaldehyde, carbon dioxide, intensity of illumination. As a result of the data, infant units showed higher concentration of formaldehyde and carbon dioxide than Indoor Air Quality Control Law. Moreover, infant units was measured higher intensity of illumination than the range of optimum illumination for infants.

• 제어로봇시스템학회논문지
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• 제22권9호
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• pp.738-744
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• 2016

In this paper, a robust visual odometry system has been proposed and implemented in an environment with dynamic illumination. Visual odometry is based on stereo images to estimate the distance to an object. It is very difficult to realize a highly accurate and stable estimation because image quality is highly dependent on the illumination, which is a major disadvantage of visual odometry. Therefore, in order to solve the problem of low performance during the feature detection phase that is caused by illumination variations, it is suggested to determine an optimal threshold value in the image binarization and to use an adaptive threshold value for feature detection. A feature point direction and a magnitude of the motion vector that is not uniform are utilized as the features. The performance of feature detection has been improved by the RANSAC algorithm. As a result, the position of a mobile robot has been estimated using the feature points. The experimental results demonstrated that the proposed approach has superior performance against illumination variations.

• 한국지능시스템학회논문지
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• 제20권6호
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• pp.780-785
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• 2010

본 논문은 물체인식이나 영상추적에 사용되는 컬러검출을 위한 GP(Genetic Programming) 기반의 컬러검출 모델을 제안한다. 기존의 컬러검출은 기본적인 RGB 모델에 대한 선형, 비선형 함수의 변환을 사용하거나, 최적화 기법이나 학습기법에 의해 조명 변화에 개선된 컬러 모델을 사용하고 있다. 하지만 대부분의 경우 색상 채널간의 간섭에 의해 다양한 색상에 대한 분류가 어렵고, 조명변화에 강인하지 못하다. 본 연구에서는 GP의 최적화된 학습기법과 모델 생성 기법을 통해 조명변화에 강인하고, 다중의 색상 검출이 가능하며, 파라미터 설정이 필요 없는 컬러 모델을 제안한다. 제안된 방법을 다양한 색상과 조명환경이 다른 영상에 대해서 기존 컬러모델과 비교 분석하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제4권6호
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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.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.36-39
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• 1997

In this paper, we described an approach to design of precision optical system for visual inspection of solder joint defects of SMC(surface mount components) on PCBs(Printed Circuit Board). The illumination system, consisting of three tiered LED lamps and one main camera and four side view camera, is implemented to generated iso-contour on the solder joint according to gradient of the soldered surface. We analyze LED design parameter such as incident angle, diameter of LED ring, and so on to acquire uniform illumination.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.162.4-162
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• 2001

This paper presents a fuzzy-based method for classification skin color object in a complex background under varying illumination Parameters of fuzzy rule base are generated using a genetic algorithm(GA). The color model is used in the YCbCr color space. We propose a unique fuzzy system in order to accommodate varying background color and illumination condition This fuzzy system approach to skin color classification is discussed along with an overview of YCbCr color space.

• Journal of Information Processing Systems
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• 제14권1호
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• pp.191-204
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• 2018

To combat the adverse impact imposed by illumination variation in the face recognition process, an effective and feasible algorithm is proposed in this paper. Firstly, an enhanced local texture feature is presented by applying the central symmetric encode principle on the fused component images acquired from the wavelet decomposition. Then the proposed local texture features are combined with Deep Belief Network (DBN) to gain robust deep features of face images under severe illumination conditions. Abundant experiments with different test schemes are conducted on both CMU-PIE and Extended Yale-B databases which contain face images under various illumination condition. Compared with the DBN, LBP combined with DBN and CSLBP combined with DBN, our proposed method achieves the most satisfying recognition rate regardless of the database used, the test scheme adopted or the illumination condition encountered, especially for the face recognition under severe illumination variation.

• 한국농공학회논문집
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• 제62권5호
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• pp.63-72
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• 2020

Solar-sharing, which is an agricultural photovoltaic system installing solar panels on the upper part of crop growing field, has especially drawn attention. Because paddy fields for cultivating crops are large flat areas, there have been various attempts to utilize solar energy for solar photovoltaic as well as growth of crops in agriculture. Solar-sharing was first proposed in Japan, and has been actively studied for optimization and practical uses. The domestic climate differs from the climate conditions in which the solar-sharing has been widely studied, therefore, it is required to develop the solar-sharing technology suitable for the domestic climate. In this study, a simulation model was developed to analyze the change of solar radiation resulted from the solar-sharing installation. Monthly solar illumination intensity and the change of illumination intensity according to the various conditions of solar panel installation were simulated. The results of monthly illumination analysis differed by altitude of the sun, which was related to season. In addition, it was analyzed that the monthly illumination decreased by up to 42% due to solar-sharing. Accordingly, it is recommended that solar-sharing should be installed as a way to maximize the efficiency of solar photovoltaic system while minimizing the decrease in solar radiation reaching the crops.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권1호
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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.