• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.3
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• pp.9-15
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• 2021

In this paper, the Embedded MEMS system to the power apparatus used Edge Impulse machine learning tools and therefore an improved predictive system design is implemented. The proposed MEMS embedded system is developed based on nRF52840 system and the sensor with 3-Axis Digital Magnetometer, I2C interface and magnetic measurable range ±120 uT, BM1422AGMV which incorporates magneto impedance elements to detect magnetic field and the ARM M4 32-bit processor controller circuit in a small package. The MEMS embedded platform is consisted with Edge Impulse Machine Learning and system driver implementation between hardware and software drivers using SensorQ which is special queue including user application temporary sensor data. In this paper by experimenting, TensorFlow machine learning training output is applied to the power apparatus for analyzing the status such as "Normal, Warning, Hazard" and predicting the performance at level of 99.6% accuracy and 0.01 loss.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.770-772
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• 2013

Edges on the images are widely used in preprocessing in various areas including recognition and detection of the object. As generally known edge detection methods, there is a method using mask and these methods are Sobel, Prewitt, Roberts, Laplacian operator and etc. Implementation of these existing edge detection methods is simple. However, when processing the impulse noise added images, the properties of edge detection is not sufficient. Accordingly, in order to compensate for the weakness of existing edge detection methods and to detect strong edges on the images which were damaged by impulse noise, the edge detection algorithm using transformed mask was proposed in this paper.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.404-406
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• 2013

An image edge has been utilized as preprocessing procedure in various field such as object detection, object recognition. there are Sobel, Prewitt, Roberts, Laplacian as conventional edge detection methods. existing methods are implement is simple, but edge detection characteristics is insufficient in impulse noise area. Therefore, to compensate the defect of conventional methods, in this paper, an edge detection algorithm using modified mask is proposed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.9
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• pp.2259-2264
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• 2014

For edge detection methods, there are Sobel, Prewitt, Roberts and Canny edge detector, and these methods have insufficient detection characteristics in the image corrupted by the impulse noise. Therefore in this paper, in order to improve these disadvantages of the previous methods and to effectively detect the edge in the impulse noise environment, using the $5{\times}5$ mask, the noise factors within the $3{\times}3$ mask based on the central pixel is determined, and depending on its status, for noise-free it is processed as is, and if noise is found, by obtaining the estimated mask using the adjacent pixels of each factor, an algorithm that detects the edge is proposed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.477-480
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• 2009

In the process of transmitting images, there are several different underlying causes of degradation that have been occuring. The main underlying cause of the degradation has been attributed to the noise. The most representive method of removal noise of image, which is caused by impulse noise, is using the SM filter. At edge the filter has a special feature which has a tendency to decrease. As a result, this paper we proposed the nonlinear filter using the form of mask and the probability of the impulse noise to restore the image considering edge quality in the impulse noise environment. And through the simulation, we compared with the existing methods and capabilties.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.6
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• pp.722-728
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• 2020

Digital image processing has been applied in a wide range of fields due to the development of IoT technology and plays an important role in data processing. Various techniques have been proposed to remove such noise, but the conventional impulse noise canceling methods are insufficient to remove noise of edge components of an image, and have a disadvantage of being greatly affected by random impulse noise. Therefore, in this paper, we propose an algorithm that effectively removes edge component noise in random impulse noise environment. The proposed algorithm calculates the threshold value by determining the noise level and switches the filtering process by comparing the reference value with the input pixel value. The proposed algorithm shows good performance in the existing method, and the simulation results show that the noise is effectively removed from the edge of the image.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.4
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• pp.973-979
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• 2011

In the transmitting process of image signal processing system, there are several different causes of degradation that have been occurring. The main cause of degradation is attributed to the noise. The most representive method of removing noise of image, which is caused by impulse noise environment, is using the SM(standard median filter). At edge, the filter has a special feature which has a tendency to decrease. As a result, we proposed a nonlinear filter that restores the image considering edge quality in the impulse noise environment. And through the simulation, we compared with the many of the conventional algorithms and the value of the PSNR(peak signal to nise ratio) is better than them and preserve the edge very well. So the nonlinear filter that proposed in this paper is excepted to help improve restoring the images that in impulse noise environment.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.4
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• pp.135-140
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• 2014

As the digital image devices are widely used, interests in the software- and the hardware-related image processing become higher and the image processing techniques are applied in various fields such as object recognition, object detection, fingerprint recognition, and etc. For the edge detections Sobel, Prewitt, Laplacian, Roberts and Canny detectors are used and these existing methods can excellently detect the edges of the images without noise. However, in the images corrupted by the impulse noise, these methods are insufficent in noise elimination characteristics, showing unsatisfactory edge detection. Therefore in this paper, in order to obtain excellent edge detection characteristics in the corrupted image by the impulse noise, an detection algorithm is porposed, which uses the central pixel of mask divided by four regions along the axis, calculates the estimated mask according to the representing pixel values in each regions, and detects the final edges by applying the estimates mask and the new directional one.

• Journal of the Korean Society of Propulsion Engineers
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• v.15 no.4
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• pp.41-47
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• 2011

Turbopump, which is a part of 75 ton open cycle liquid rocket engine has a super sonic impulse turbine. This paper investigated the leading edge thickness effect on the turbine performance experimently. Two rotors were tested with the different leading edge thickness. The ratios (rotor thickness to Pitch) are 1.9 and 1.4 times to 30 ton turbine rotor. As a result, a rotor with 1.4 times ratio had a 1.5% higher efficiency gain than a rotor with 1.9 times ratio. The pressure ratio with the maximum efficiency on the same rotational speed was increased to the full expansion ratio of nozzle.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.3
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• pp.84-96
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• 1997

In this paper an efficient morphologica algorithm for reducing gaussian and impulse noise in gray-scale image is presented. Based on the edge information the input image is partitioned into a flat region and an edge region, then different algorithms are selectively applied to each region. in case of impulse noise, MGR (morphologica grayscale reconstruction) algorithm with directional SE (structuring element) is applied to the flat region. For theedge region opening-closing (closing-opening) is used instead of dialation (erosion), so that the remaining noise around large objects can be removed. In case of gaussian noise, 5*5 OCCO(opening closing closing opening) and 3*3 DMF(directional morphological filter ) are used for the flat region and the edgeregion, respectively. In order to remove discontinuity at the edge boundary, the algorithm uses 3*3 OCCO around the edge region to reconstruct the final image. Experimetnal results have shown that the proposed algorithm achieves a high performance in terms of noise removal, detail preservation, and NMSE.