• Title/Summary/Keyword: Fast Computation

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Development of a Fruit Grader using Black/White Image Processing System(I) - Determining the Size and Coloration - (흑백영상처리장치를 이용한 과실선별기 개발에 관한 연구(I) - 크기 및 색택 판정 -)

  • Noh, S.H.;Lee, J.W.;Lee, S.H.
    • Journal of Biosystems Engineering
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    • v.17 no.4
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    • pp.354-362
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    • 1992
  • This study was intended to examine feasibility of sizing and color grading of Fuji apple with black/white image processing system, to develop a device with which the whole surface of an apple could be captured by one camera, and to develop an algorithm for a high speed sorting. The results are summarized as follows : 1. The black/white image processing system used in this study showed a maximum error of 1.3% in area measurement with a reference figure while the focusing point of camera and location of the reference figure were changed within a certain range. 2. As the result of evaluating four automatic image segmentation algorithms with apple images, Histogram Clustering Method was the best in terms of computation time and accuracy. 3. The fast algorithm for analyzing size and coloration of apple was developed. 4. The whole surface of an apple could be captured in an image frame with two mirrors installed on the both sides of the sample. The total area of the image representing the whole surface showed a correlation of 0.995 with the weight of apple. 5. The gray level when a particular band pass filter was mounted on the camera showed high correlation with 'L' and 'a' values of Hunt color scale and could represent the coloration of apple.

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Real Time Neural Controller Design of Industrial Robot Using Digital Signal Processors (디지탈 신호 처리기를 사용한 산업용 로봇의 실시간 뉴럴 제어기 설계)

  • 김용태;한성현
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1996.11a
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    • pp.759-763
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    • 1996
  • This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

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VLSI Architecture of a Recursive LMS Filter Based on a Cyclo-static Scheduler (Cyclo-static 스케줄러를 이용한 재귀형 LMS Filter의 VLSI 구조)

  • Kim, Hyeong-Kyo
    • Journal of the Institute of Convergence Signal Processing
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    • v.8 no.1
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    • pp.73-77
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    • 2007
  • In this paper, we propose a VLSI architecture of an LMS filter based on a Cyclo-static scheduler for fast computation of LMS filteing algorithm which is widely used in adptive filtering area. This process is composed of two steps: scheduling and circuit synthesis. The scheduling step accepts a fully specified flow graph(FSFG) as an input, and generates an optimal Cyclo-static schedule in the sense of the sampling rate, the number of processors, and the input-output delay. Then the generated schedule is transformed so that the number of communication edges between the processors. The circuit synthesis part translates the modified schedule into a complete circuit diagram by performing resource allocations. The VLSI layout generation can be performed easily by an existing silicon compiler.

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CUDA based parallel design of a shot change detection algorithm using frame segmentation and object movement

  • Kim, Seung-Hyun;Lee, Joon-Goo;Hwang, Doo-Sung
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.7
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    • pp.9-16
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    • 2015
  • This paper proposes the parallel design of a shot change detection algorithm using frame segmentation and moving blocks. In the proposed approach, the high parallel processing components, such as frame histogram calculation, block histogram calculation, Otsu threshold setting function, frame moving operation, and block histogram comparison, are designed in parallel for NVIDIA GPU. In order to minimize memory access delay time and guarantee fast computation, the output of a GPU kernel becomes the input data of another kernel in a pipeline way using the shared memory of GPU. In addition, the optimal sizes of CUDA processing blocks and threads are estimated through the prior experiments. In the experimental test of the proposed shot change detection algorithm, the detection rate of the GPU based parallel algorithm is the same as that of the CPU based algorithm, but the average of processing time speeds up about 6~8 times.

Equivalence Principles Based Skin Deformation of Character Animation

  • You, L.H.;Chaudhry, E.;You, X.Y.;Zhang, Jian J.
    • International Journal of CAD/CAM
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    • v.9 no.1
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    • pp.61-69
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    • 2010
  • Based on the equivalence principles of physical properties, geometric properties and externally applied forces between a surface and the corresponding curves, we present a fast physics and example based skin deformation method for character animation in this paper. The main idea is to represent the skin surface and its deformations with a group of curves whose computation incurs much less computing overheads than the direct surface-based approach. The geometric and physical properties together with externally applied forces of the curves are determined from those of the surface defined by these curves according to the equivalence principles between the surface and the curves. This ensures the curve-based approach is equivalent to the original problem. A fourth order ordinary differential equation is introduced to describe the deformations of the curves between two example skin shapes which relates geometric and physical properties and externally applied forces to shape changes of the curves. The skin deformation is determined from these deformed curves. Several examples are given in this paper to demonstrate the application of the method.

Thickness and clearance visualization based on distance field of 3D objects

  • Inui, Masatomo;Umezun, Nobuyuki;Wakasaki, Kazuma;Sato, Shunsuke
    • Journal of Computational Design and Engineering
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    • v.2 no.3
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    • pp.183-194
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    • 2015
  • This paper proposes a novel method for visualizing the thickness and clearance of 3D objects in a polyhedral representation. The proposed method uses the distance field of the objects in the visualization. A parallel algorithm is developed for constructing the distance field of polyhedral objects using the GPU. The distance between a voxel and the surface polygons of the model is computed many times in the distance field construction. Similar sets of polygons are usually selected as close polygons for close voxels. By using this spatial coherence, a parallel algorithm is designed to compute the distances between a cluster of close voxels and the polygons selected by the culling operation so that the fast shared memory mechanism of the GPU can be fully utilized. The thickness/clearance of the objects is visualized by distributing points on the visible surfaces of the objects and painting them with a unique color corresponding to the thickness/clearance values at those points. A modified ray casting method is developed for computing the thickness/clearance using the distance field of the objects. A system based on these algorithms can compute the distance field of complex objects within a few minutes for most cases. After the distance field construction, thickness/clearance visualization at a near interactive rate is achieved.

ANALOG COMPUTING FOR A NEW NUCLEAR REACTOR DYNAMIC MODEL BASED ON A TIME-DEPENDENT SECOND ORDER FORM OF THE NEUTRON TRANSPORT EQUATION

  • Pirouzmand, Ahmad;Hadad, Kamal;Suh, Kune Y.
    • Nuclear Engineering and Technology
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    • v.43 no.3
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    • pp.243-256
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    • 2011
  • This paper considers the concept of analog computing based on a cellular neural network (CNN) paradigm to simulate nuclear reactor dynamics using a time-dependent second order form of the neutron transport equation. Instead of solving nuclear reactor dynamic equations numerically, which is time-consuming and suffers from such weaknesses as vulnerability to transient phenomena, accumulation of round-off errors and floating-point overflows, use is made of a new method based on a cellular neural network. The state-of-the-art shows the CNN as being an alternative solution to the conventional numerical computation method. Indeed CNN is an analog computing paradigm that performs ultra-fast calculations and provides accurate results. In this study use is made of the CNN model to simulate the space-time response of scalar flux distribution in steady state and transient conditions. The CNN model also is used to simulate step perturbation in the core. The accuracy and capability of the CNN model are examined in 2D Cartesian geometry for two fixed source problems, a mini-BWR assembly, and a TWIGL Seed/Blanket problem. We also use the CNN model concurrently for a typical small PWR assembly to simulate the effect of temperature feedback, poisons, and control rods on the scalar flux distribution.

Development of Precise Localization System for Autonomous Mobile Robots using Multiple Ultrasonic Transmitters and Receivers in Indoor Environments (다수의 초음파 송수신기를 이용한 이동 로봇의 정밀 실내 위치인식 시스템의 개발)

  • Kim, Yong-Hwi;Song, Ui-Kyu;Kim, Byung-Kook
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.4
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    • pp.353-361
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    • 2011
  • A precise embedded ultrasonic localization system is developed for autonomous mobile robots in indoor environments, which is essential for autonomous navigation of mobile robots with various tasks. Although ultrasonic sensors are more cost-effective than other sensors such as LRF (Laser Range Finder) and vision, they suffer inaccuracy and directional ambiguity. First, we apply the matched filter to measure the distance precisely. For resolving the computational complexity of the matched filter for embedded systems, we propose a new matched filter algorithm with fast computation in three points of view. Second, we propose an accurate ultrasonic localization system which consists of three ultrasonic receivers on the mobile robot and two or more transmitters on the ceiling. Last, we add an extended Kalman filter to estimate position and orientation. Various simulations and experimental results show the effectiveness of the proposed system.

Korean continuous digit speech recognition by multilayer perceptron using KL transformation (KL 변환을 이용한 multilayer perceptron에 의한 한국어 연속 숫자음 인식)

  • 박정선;권장우;권정상;이응혁;홍승홍
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.8
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    • pp.105-113
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    • 1996
  • In this paper, a new korean digita speech recognition technique was proposed using muktolayer perceptron (MLP). In spite of its weakness in dynamic signal recognition, MLP was adapted for this model, cecause korean syllable could give static features. It is so simle in its structure and fast in its computing that MLP was used to the suggested system. MLP's input vectors was transformed using karhunen-loeve transformation (KLT), which compress signal successfully without losin gits separateness, but its physical properties is changed. Because the suggested technique could extract static features while it is not affected from the changes of syllable lengths, it is effectively useful for korean numeric recognition system. Without decreasing classification rates, we can save the time and memory size for computation using KLT. The proposed feature extraction technique extracts same size of features form the tow same parts, front and end of a syllable. This technique makes frames, where features are extracted, using unique size of windows. It could be applied for continuous speech recognition that was not easy for the normal neural network recognition system.

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Efficient Method of Detecting Blurry Images

  • Tsomko, Elena;Kim, Hyoung-Joong;Paik, Joon-Ki;Yeo, In-Kwon
    • Journal of Ubiquitous Convergence Technology
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    • v.2 no.1
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    • pp.27-39
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    • 2008
  • In this paper we present a simple, efficient method for detecting the blurry photographs. Recently many digital cameras are equipped with various auto-focusing functions to help users take well-focused pictures as easily as possible. In addition, motion compensation devices are able to compensate motion causing blurriness in the images. However, digital pictures can be degraded by limited contrast, inappropriate exposure, imperfection of auto-focusing or motion compensating devices, unskillfulness of the photographers, and so on. In order to decide whether to process the images or not, or whether to delete them or not, reliable measure of image degradation to detect blurry images from sharp ones is needed. This paper presents a blurriness/sharpness measure, and demonstrates its feasibility by using extensive experiments. This method is fast, easy to implement and accurate. Regardless of the detection accuracy, the proposed measure in this paper is not demanding in computation time. Needless to say, this measure can be used for various imaging applications including auto-focusing and astigmatism correction.

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