• Title/Summary/Keyword: Neuro-image

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Speckle Reduction based on Neuro-Fuzzy Technique (뉴로-퍼지를 이용한 스펙클 제거)

  • Kil, Se-Kee;Jeon, Yu-Yong;Oh, Hyung-Seok;Nishimura, Toshihiro;Kwon, Jang-Woo;Lee, Sang-Min
    • Journal of IKEEE
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    • v.12 no.3
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    • pp.158-166
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    • 2008
  • Medical ultrasound has benefits in mobility and safety than any other medical techniques such as X-ray, CT and MRI but has speckle noise which decrease the ability of an observer to distinguish the fine details in diagnostic examination. But simple removing of speckle often causes losing boundary information. Then, in this paper, we presented a novel neuro-fuzzy method which could remove speckle efficiently without loss of boundary information. Proposed method consists of image clustering by fuzzy algorithm and image processingby neural networks which was learned by back propagation. From the experiments for simulation image and real ultrasound image, we could verify the proposed method.

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RECOGNITION ALGORITHM OF DRIED OAK MUSHROOM GRADINGS USING GRAY LEVEL IMAGES

  • Lee, C.H.;Hwang, H.
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 1996.06c
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    • pp.773-779
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    • 1996
  • Dried oak mushroom have complex and various visual features. Grading and sorting of dried oak mushrooms has been done by the human expert. Though actions involved in human grading looked simple, a decision making underneath the simple action comes from the result of the complex neural processing of the visual image. Through processing details involved in human visual recognition has not been fully investigated yet, it might say human can recognize objects via one of three ways such as extracting specific features or just image itself without extracting those features or in a combined manner. In most cases, extracting some special quantitative features from the camera image requires complex algorithms and processing of the gray level image requires the heavy computing load. This fact can be worse especially in dealing with nonuniform, irregular and fuzzy shaped agricultural products, resulting in poor performance because of the sensitiveness to the crisp criteria or specific ules set up by algorithms. Also restriction of the real time processing often forces to use binary segmentation but in that case some important information of the object can be lost. In this paper, the neuro net based real time recognition algorithm was proposed without extracting any visual feature but using only the directly captured raw gray images. Specially formated adaptable size of grids was proposed for the network input. The compensation of illumination was also done to accomodate the variable lighting environment. The proposed grading scheme showed very successful results.

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Face Recognition Using a Neuro-Fuzzy Algorithm (뉴로-퍼지 알고리듬을 이용한 얼굴인식)

  • 이상영;함영국;박래홍
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.32B no.1
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    • pp.50-63
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    • 1995
  • In this paper, we propose a face recognition method using a neuro-fuzzy algorithm. In the preprocessing step, we extract the face part from the background image by tracking face boundaries. Then based on the a priori knowledge of human faces we extract the features such as widths of eyes and mouth, and distances from eye to nose and nose to mouth. In the recognition step. We use a neuro-fuzzy algorithm that employs a fuzzy membership function and modified error backpropagation algorithm. The former absorbs the variation of feature values and the latter shows good learning efficiency. Computer simulation results with 20 persons show that the proposed method gives higher recognition rate than the conventional ones.

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Control of Convergence for Deflection Yoke Using Neuro-Fuzzy Model (뉴로 퍼지 모델을 이용한 편향요크의 RGB색 일치에 대한 제어)

  • 정병묵;임윤규;정창욱
    • Journal of the Korean Society for Precision Engineering
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    • v.15 no.5
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    • pp.19-27
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    • 1998
  • Color Display Tube (CDT) used in computer monitors, consists of many components. Deflection Yoke(DY) among them supplies the vertical and horizontal magnetic fields so that the spatial trajectories of electron beams are deflected according to the synchronization signals. If the magnetic fields are not correctly formed, there will be color blurring or blooming by a mis-convergence of each beam and the color image on screen may not be clear. Therefore, in the manufacture of DY. its quality is strictly examined to get the desired convergence and the occurred mis-convergence can be cured by sticking ferrite sheets on the inner part of DY. However, because it needs expert's knowledge and experience to find the proper position of the sheet, this article introduces an intelligent controller that the knowledge-base represented by a neuro-fuzzy model is used to find the optimal position of the ferrite sheet for the convergence.

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Visual servoing based on neuro-fuzzy model

  • Jun, Hyo-Byung;Sim, Kwee-Bo
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.712-715
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    • 1997
  • In image jacobian based visual servoing, generally, inverse jacobian should be calculated by complicated coordinate transformations. These are required excessive computation and the singularity of the image jacobian should be considered. This paper presents a visual servoing to control the pose of the robotic manipulator for tracking and grasping 3-D moving object whose pose and motion parameters are unknown. Because the object is in motion tracking and grasping must be done on-line and the controller must have continuous learning ability. In order to estimate parameters of a moving object we use the kalman filter. And for tracking and grasping a moving object we use a fuzzy inference based reinforcement learning algorithm of dynamic recurrent neural networks. Computer simulation results are presented to demonstrate the performance of this visual servoing

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A Study on the Multi-sensory Stimulation of Aroma and Color Temperature effects on Neuro-energy (아로마 및 색온도의 다감각자극이 뉴로에너지에 미치는 영향)

  • Kim, Jung-Min;Seo, Kwang-Soo;Kim, Myung-Ho
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.5
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    • pp.3579-3586
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    • 2015
  • In this study, EEG, HRV, and Vibra image were compared and analyzed in the environmental test room due to stimulation of aroma and color temperature. The condition of the environmental test room was in temperature $25[^{\circ}C]$, relative humidity 50[RH%], air current speed 0.02[m/s] and illuminance 1000[lux] with setting up different sensory stimulation condition which are before exposure, single-sensory stimulation of Jasmine scent, single-sensory stimulation of RED color lighting, and multi-sensory stimulation of Jasmine scent and RED color lighting. The result of this study, at multi-sensory stimulation of Jasmine scent and RED color lighting, relative $S{\alpha}$ wave, SEF50, $SMR/{\theta}$ and SDNN were revitalized, and both sides ${\alpha}$ wave asymmetry index, stress index, fatigue degree, and HRT were decreased. Also, Viba image of tension/anxiety and stress were declined. Therefore multi-sensory stimulation of Jasmine scent and RED color lighting effects to increase the Neuro-energy like amenity, productivity of work efficiency, and concentration.

Distance Measurement Using the Kinect Sensor with Neuro-image Processing

  • Sharma, Kajal
    • IEIE Transactions on Smart Processing and Computing
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    • v.4 no.6
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    • pp.379-383
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    • 2015
  • This paper presents an approach to detect object distance with the use of the recently developed low-cost Kinect sensor. The technique is based on Kinect color depth-image processing and can be used to design various computer-vision applications, such as object recognition, video surveillance, and autonomous path finding. The proposed technique uses keypoint feature detection in the Kinect depth image and advantages of depth pixels to directly obtain the feature distance in the depth images. This highly reduces the computational overhead and obtains the pixel distance in the Kinect captured images.

Image-guided Stereotactic Neurosurgery: Practices and Pitfalls

  • Jung, Na Young;Kim, Minsoo;Kim, Young Goo;Jung, Hyun Ho;Chang, Jin Woo;Park, Yong Gou;Chang, Won Seok
    • Journal of International Society for Simulation Surgery
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    • v.2 no.2
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    • pp.58-63
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    • 2015
  • Image-guided neurosurgery (IGN) is a technique for localizing objects of surgical interest within the brain. In the past, its main use was placement of electrodes; however, the advent of computed tomography has led to a rebirth of IGN. Advances in computing techniques and neuroimaging tools allow improved surgical planning and intraoperative information. IGN influences many neurosurgical fields including neuro-oncology, functional disease, and radiosurgery. As development continues, several problems remain to be solved. This article provides a general overview of IGN with a brief discussion of future directions.

A Study on the Indoor Temperature effects on Neuro-energy (실내 온도가 뉴로에너지에 미치는 영향에 관한 연구)

  • Kim, Jung-Min;Kim, Myung-Ho
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.4
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    • pp.2436-2442
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    • 2014
  • In this study, EEG, HRV, and Vibra image were compared and analyzed in the environmental test room due to variation of temperature. The condition of the environmental test room was in relative humidity 50[RH%], air current speed 0.02[m/s] and illuminance 1000[lux] with setting up different temperatures from $18[^{\circ}C]$ to $31[^{\circ}C]$. At temperature $25[^{\circ}C]$, relative $M{\alpha}$ wave, relative $M{\beta}$ wave, $\frac{SMR}{\theta}$, and SDNN were revitalized, and both sides ${\alpha}$ wave asymmetry index $A_2$, HRT, stress index, and fatigue degree were decreased. Therefore, it was found that temperature $25[^{\circ}C]$ effects to increase the Neuro-energy like amenity, productivity, and concentration.