• Title/Summary/Keyword: Illumination system

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Parallel Multi-task Cascade Convolution Neural Network Optimization Algorithm for Real-time Dynamic Face Recognition

  • Jiang, Bin;Ren, Qiang;Dai, Fei;Zhou, Tian;Gui, Guan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.10
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    • pp.4117-4135
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    • 2020
  • Due to the angle of view, illumination and scene diversity, real-time dynamic face detection and recognition is no small difficulty in those unrestricted environments. In this study, we used the intrinsic correlation between detection and calibration, using a multi-task cascaded convolutional neural network(MTCNN) to improve the efficiency of face recognition, and the output of each core network is mapped in parallel to a compact Euclidean space, where distance represents the similarity of facial features, so that the target face can be identified as quickly as possible, without waiting for all network iteration calculations to complete the recognition results. And after the angle of the target face and the illumination change, the correlation between the recognition results can be well obtained. In the actual application scenario, we use a multi-camera real-time monitoring system to perform face matching and recognition using successive frames acquired from different angles. The effectiveness of the method was verified by several real-time monitoring experiments, and good results were obtained.

A study of LED light control system application based on Ubiquitous sensor network (유비쿼터스 센서 네트워크 기반 LED 조명제어시스템 적용에 관한 연구)

  • Lee, An-kyu;Park, Byung-don;Gil, Jun-pyo;Shin, Gang-wook;Park, Hye-Mi
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.10a
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    • pp.188-191
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    • 2013
  • In this paper, in order to economize energy inside the vertical-type water treatment plant, a chamber-illumination-LED control board, which operates via nature light or human's touches, is proposed. Moreover, this illumination control process is contrived to be wirelessly monitored in real-rime. In addition, Zigbee communication code is programmed to implement the control board's function of wireless data transmission and automatic LED brightness control. The presented control method contrives brightness to be adjusted in real-time by dimming control, which means nature light changes control, so that the interior energy can realize the maximum energy conservation.

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A Study on Light Quality of LED for Control of Light Intensity (광 강도 제어에 따른 LED의 광질에 관한 연구)

  • Park, Sang-Hee;An, Jun-Chul;Heo, Jung-Wook;Choi, Han-Ko;Choi, Sung-Dae
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.11 no.6
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    • pp.175-182
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    • 2012
  • Light characteristics of the monochromatic red(R), blue(B), green(G) and white(W) and the mixed LED (B-R LED) were investigated by light control a Spectrometer-MMS1 and an illuminometer. The power consumption of each LED was 1W and R LED has five wavelength bands(600nm, 640nm, 660nm, 680nm, 750nm). The light intensity of each LED was changed in a range 10~100%. As a results, the wavelength and the spectrum distribution of R LED increase with increasing light intensity but the wavelength of B, G, W LED decreases. It was found that illumination of each mononochromatic and B-R LED increases linearly with increasing light intensity. It was confirmed that the illumination intensity of R-B light has greater values than those obtained by monochromatic light at the same conditions.

Determination of Leaf Color and Health State of Lettuce using Machine Vision (기계시각을 이용한 상추의 엽색 및 건강상태 판정)

  • Lee, J.W.
    • Journal of Biosystems Engineering
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    • v.32 no.4
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    • pp.256-262
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    • 2007
  • Image processing systems have been used to measure the plant parameters such as size, shape and structure of plants. There are yet some limited applications for evaluating plant colors due to illumination conditions. This study was focused to present adaptive methods to analyze plant leaf color regardless of illumination conditions. Color patches attached on the calibration bars were selected to represent leaf colors of lettuces and to test a possibility of health monitoring of lettuces. Repeatability of assigning leaf colors to color patches was investigated by two-tailed t-test for paired comparison. It resulted that there were no differences of assignment histogram between two images of one lettuce that were acquired at different light conditions. It supported that use of the calibration bars proposed for leaf color analysis provided color constancy, which was one of the most important issues in a video color analysis. A health discrimination equation was developed to classify lettuces into one of two classes, SOUND group and POOR group, using the machine vision. The classification accuracy of the developed health discrimination equation was 80.8%, compared to farmers' decision. This study could provide a feasible method to develop a standard color chart for evaluating leaf colors of plants and plant health monitoring system using the machine vision.

A Vehicular License Plate Recognition Framework For Skewed Images

  • Arafat, M.Y.;Khairuddin, A.S.M.;Paramesran, R.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.11
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    • pp.5522-5540
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    • 2018
  • Vehicular license plate (LP) recognition system has risen as a significant field of research recently because various explorations are currently being conducted by the researchers to cope with the challenges of LPs which include different illumination and angular situations. This research focused on restricted conditions such as using image of only one vehicle, stationary background, no angular adjustment of the skewed images. A real time vehicular LP recognition scheme is proposed for the skewed images for detection, segmentation and recognition of LP. In this research, a polar co-ordinate transformation procedure is implemented to adjust the skewed vehicular images. Besides that, window scanning procedure is utilized for the candidate localization that is based on the texture characteristics of the image. Then, connected component analysis (CCA) is implemented to the binary image for character segmentation where the pixels get connected in an eight-point neighbourhood process. Finally, optical character recognition is implemented for the recognition of the characters. For measuring the performance of this experiment, 300 skewed images of different illumination conditions with various tilt angles have been tested. The results show that proposed method able to achieve accuracy of 96.3% in localizing, 95.4% in segmenting and 94.2% in recognizing the LPs with an average localization time of 0.52s.

Design of Robust Face Recognition System with Illumination Variation Realized with the Aid of CT Preprocessing Method (CT 전처리 기법을 이용하여 조명변화에 강인한 얼굴인식 시스템 설계)

  • Jin, Yong-Tak;Oh, Sung-Kwun;Kim, Hyun-Ki
    • Journal of the Korean Institute of Intelligent Systems
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    • v.25 no.1
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    • pp.91-96
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    • 2015
  • In this study, we introduce robust face recognition system with illumination variation realized with the aid of CT preprocessing method. As preprocessing algorithm, Census Transform(CT) algorithm is used to extract locally facial features under unilluminated condition. The dimension reduction of the preprocessed data is carried out by using $(2D)^2$PCA which is the extended type of PCA. Feature data extracted through dimension algorithm is used as the inputs of proposed radial basis function neural networks. The hidden layer of the radial basis function neural networks(RBFNN) is built up by fuzzy c-means(FCM) clustering algorithm and the connection weights of the networks are described as the coefficients of linear polynomial function. The essential design parameters (including the number of inputs and fuzzification coefficient) of the proposed networks are optimized by means of artificial bee colony(ABC) algorithm. This study is experimented with both Yale Face database B and CMU PIE database to evaluate the performance of the proposed system.

A Fast and Robust License Plate Detection Algorithm Based on Two-stage Cascade AdaBoost

  • Sarker, Md. Mostafa Kamal;Yoon, Sook;Park, Dong Sun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.10
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    • pp.3490-3507
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    • 2014
  • License plate detection (LPD) is one of the most important aspects of an automatic license plate recognition system. Although there have been some successful license plate recognition (LPR) methods in past decades, it is still a challenging problem because of the diversity of plate formats and outdoor illumination conditions in image acquisition. Because the accurate detection of license plates under different conditions directly affects overall recognition system accuracy, different methods have been developed for LPD systems. In this paper, we propose a license plate detection method that is rapid and robust against variation, especially variations in illumination conditions. Taking the aspects of accuracy and speed into consideration, the proposed system consists of two stages. For each stage, Haar-like features are used to compute and select features from license plate images and a cascade classifier based on the concatenation of classifiers where each classifier is trained by an AdaBoost algorithm is used to classify parts of an image within a search window as either license plate or non-license plate. And it is followed by connected component analysis (CCA) for eliminating false positives. The two stages use different image preprocessing blocks: image preprocessing without adaptive thresholding for the first stage and image preprocessing with adaptive thresholding for the second stage. The method is faster and more accurate than most existing methods used in LPD. Experimental results demonstrate that the LPD rate is 98.38% and the average computational time is 54.64 ms.

Vision Inspection Method Development which Improves Accuracy By using Power-Law Transformation and Histogram Specification (멱함수 변환과 히스토그램 지정을 사용하여 정확도를 향상시킨 Vision 검사 방법 개발)

  • Huh, Kyung-Moo;Park, Se-Hyuk;Kang, Su-Min
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.44 no.5
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    • pp.11-17
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    • 2007
  • The appearance inspection of various electronic products and parts has been executed by the eyesight of human. But inspection by eyesight can't bring about uniform inspection result. Because the appearance inspection result by eyesight of human is changed by condition of physical and spirit of the checker. So machine vision inspection system is currently used to many appearance inspection fields instead of the checker. However the inspection result of machine vision is changed by the illumination of workplace. Therefore we have used a power-law transformation and histogram specification in this paper for improvement of vision inspection accuracy. As a result of these power-law transformation and histogram specification algorithm, we could increase the exactness of vision inspection and prevent system error from physical and spirit condition of human. Also this system has been developed only using PC, CCD Camera and Visual C++ for universal workplace.

Simulation of Characteristics of Lens and Light Pipe for High Concentration Solar PV System (고집광 태양광 발전을 위한 렌즈 및 광 파이프 특성 시뮬레이션)

  • Ryu, Kwnag-Sun;Shin, Goo-Hwan;Cha, Won-Ho;Myung, Noh-Hoon;Kim, Young-Sik;Chung, Ho-Yoon;Kim, Dong-Kyun;Kang, Gi-Hwan
    • 한국태양에너지학회:학술대회논문집
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    • 2011.04a
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    • pp.282-286
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    • 2011
  • The artificial increase in the solar intensity incident on solar cells using lenses or mirrors can allow solar cells to generate equivalent power with a lower cost. In application areas of Fresnel lenses as solar concentrators, several variations of design were devised and tested. Some PV systems still use commercially available flat Fresnel lenses as concentrators. In this study, we designed and optimized flat Fresnel lens and the 'light pipe' to develop 500X concentrated solar PV system. We performed rigorous ray tracing simulation of the flat Fresnel lens and light-pipe. The light-pipe can play imporatant roles of redistributing solar energy at the solar cell and increase the mechanical tolerance so that it can increase the lifetime of the high-concentration solar PV system and decrease the cost of manufacturing. To investigate the sensitivity of the solar power generated by the concentrated solar PV according to the performance of lens and light pipe, we performed raytracing and executed a simulation of electrical performance of the solar cell when it is exposed to the non-uniform illumination. We could conclude that we can generate 95 % or more energy compared with the energy that can be generated by perfectly uniform illumination once the total energy is given the same.

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Low Carbon and Green Growth Cave Lightings with SOLAR-LED System (SOLAR-LED 시스템과 저탄소녹색동굴조명)

  • Soh, Dea-Wha;Kang, Sang-Tack;Soh, Hyun-Jun
    • Journal of the Speleological Society of Korea
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    • no.95
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    • pp.15-21
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    • 2009
  • Global village warming and carbon dioxide CO2 gas, and the human efforts for their healing and necessary alternative technology would be much more difficult things than that of making necessary funds and efforts to lay to sleep angry nature on the earth. The limited natural resources of fossil fuel would be dried up in several decades, and the intensity of diplomatic negotiations for natural resource guarantee among countries may be showed looking alike an war. The drain of fossil fuel called a new word of alternative policy like an environment-friendly green-growth, and the solar-cell and lighting technology for the solar energy applications were developed still more repeatedly day by day from oil lantern to LED high-tech illumination in great economy. Therefore, it was studied that the low-carbon green-growth illumination technology in cave applications with SOLAR-LED system which was produced and unified in connection with solar-cell and LED from the semiconductor production technology, and it was also clarified in necessary with useful cave lighting in heatless and with no photosynthesis of plant production in underground space.