• Journal of Advanced Navigation Technology
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• v.9 no.1
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• pp.10-18
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• 2005

These studies developed system as well as its algorithm which can measure traffic flow and vehicle speed on the highway as well as road by using industrial television(ITV) system. This algorithm used the real time processing of dynamic images. The processing algorithm of dynamic images is developed and proved its validity by frame grabber. Frame grabber can process the information of a small number of sample points only instead of the whole pixel of the images. In the techniques of this algorithm, we made approximate contour of vehicle by allocating sampling points in cross-direction of image, and recognized top of contour of vehicle. Applying these technique, we measured the number of passing vehicles of one lane as well as multilane. Speed of each vehicle is measured by computing the time difference between a pair of sample points on two sample points lines.

• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.5
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• pp.658-665
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• 2014

The neural stimulators have been employed to the visual prostheses system based on the functional electrical stimulation (FES). Due to the size limitation of the implantable device, the smaller area of the unit current driver pixel is highly desired for higher resolution current stimulation system. This paper presents a 16-channel compact current-mode neural stimulator IC with digital to analog converter (DAC) sharing scheme for artificial retinal prostheses. The individual pixel circuits in the stimulator IC share a single 6 bit DAC using the sample-and-hold scheme. The DAC sharing scheme enables the simultaneous stimulation on multiple active pixels with a single DAC while maintaining small size and low power. The layout size of the stimulator circuit with the DAC sharing scheme is reduced to be 51.98 %, compared to the conventional scheme. The stimulator IC is designed using standard $0.18{\mu}m$ 1P6M process. The chip size except the I/O cells is $437{\mu}m{\times}501{\mu}m$.

• Spatial Information Research
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• v.18 no.3
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• pp.73-83
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• 2010

This study presents a method to segment an image, employing the statistics observed at each pixel location across sequential frame images. In the acquisition and analysis of spatial information, utilization of digital image processing technique has very important implications. Various image segmentation techniques have been presented to distinguish the area of digital images. In this study, based on the analysis of the spectroscopic characteristics of sequential frame images that had been previously researched, an image segmentation method was proposed by using the randomness occurring among a sequence of frame images for a same scene. First of all, we computed the mean and standard deviation values at each pixel and found reliable pixels to determine seed points using their standard deviation value. For segmenting an image into individual regions, we conducted region growing based on a T-test between reference and candidate sample sets. A comparative analysis was conducted to assure the performance of the proposed method with reference to a previous method. From a set of experimental results, it is confirmed that the proposed method using a sequence of frame images segments a scene better than a method using a single frame image.

• The Korean Journal of Applied Statistics
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• v.23 no.3
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• pp.595-607
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• 2010

This paper addresses the problem of reducing the speckle noise in SAR images by wavelet transformation, using a non-local means(NLM) filter originated for Gaussian noise removal. Log-transformed SAR image makes multiplicative speckle noise additive. Thus, non-local means filtering and wavelet thresholding are used to reduce the additive noise, followed by an exponential transformation. NLM filter is an image denoising method that replaces each pixel by a weighted average of all the similarly pixels in the image. But the NLM filter takes an acceptable amount of time to perform the process for all possible pairs of pixels. This paper, also proposes an alternative strategy that uses the t-test more efficiently to eliminate pixel pairs that are dissimilar. Extensive simulations showed that the proposed filter outperforms many existing filters terms of quantitative measures such as PSNR and DSSIM as well as qualitative judgments of image quality and the computational time required to restore images.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.227-235
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• 2000

Agricultural products are easily deformable its shape because of some external forces. However, these force behavior is difficult to measure quantitatively. Until now, many researches on the mechanical property was performed with various methods such as material testing, chemical analysis and non-destructive methods. In order to investigate force behavior on the cellular unit of agricultural products, electro-microscope based 3D image processing method will contribute to analysis of plant cells behavior. Before image measurement of plant cells, plant sample was cut off cross-sectioned area in a size of almost 300-400 ${\mu}$ m units using the micron thickness device, and some of preprocessing procedure was performed with fixing and dyeing. However, the wall structure of plant cell is closely neighbor each other, it is necessary to separate its boundary pixel. Therefore, image merging and shrinking algorithm was adopted to avoid disconnection. After then, boundary pixel was traced through thinning algorithm. Each image from the electro-microscope has a information of x,y position and its height along the z axis cross sectioned image plane. 3D image was constructed using the continuous image combination. Major feature was acquired from a fault image and measured area, thickness of cell wall, shape and unit cell volume. The shape of plant cell was consist of multiple facet shape. Through this measured information, it is possible to construct for structure shape of unit plant cell. This micro unit image processing techniques will contribute to the filed of agricultural mechanical property and will use to construct unit cell model of each agricultural products and information of boundary will use for finite element analysis on unit cell image.

• Aerospace Engineering and Technology
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• v.10 no.2
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• pp.154-162
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• 2011

The KOrea Multi-Purpose Satellite-3 (KOMPSAT-3) provides 0.7 m Ground Sample Distance (GSD) panchromatic image and 2.8 m GSD multi-spectral image data for various applications. The KOMPSAT-3 system data will be applied in the field of earth observations, covering land, sea, coastal zones, and Geographic Information Systems (GIS). In order to keep the swath width of 15km at nadir view of KOMPSAT-3, CCD consist of approximately 24,020 pixels excluding 20 dark pixels at both sides and has overlap region. Because there are no CCD-line sensors with a pixel size of $7{\mu}m$, the field of view is separated into 2 parts and imaged on 2 detectors, each with 12,080 pixels. Therefore, 2 detectors have different geometric characteristic. This paper provides image simulation for geometric characteristics analysis of overlapping area of KOMPSAT-3 using KOMPSAT-2 image data.

• Journal of Drive and Control
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• v.20 no.2
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• pp.15-23
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• 2023

In this study, two-dimensional location of crops for auto weeding was detected using deep learning. To construct a dataset for soybean detection, an image-capturing system was developed using a mono camera and single-board computer and the system was mounted on a weeding robot to collect soybean images. A dataset was constructed by extracting RoI (region of interest) from the raw image and each sample was labeled with soybean and the background for classification learning. The deep learning model consisted of four convolutional layers and was trained with a weakly supervised learning method that can provide object localization only using image-level labeling. Localization of the soybean area can be visualized via CAM and the two-dimensional position of the soybean was estimated by clustering the pixels associated with the soybean area and transforming the pixel coordinates to world coordinates. The actual position, which is determined manually as pixel coordinates in the image was evaluated and performances were 6.6(X-axis), 5.1(Y-axis) and 1.2(X-axis), 2.2(Y-axis) for MSE and RMSE about world coordinates, respectively. From the results, we confirmed that the center position of the soybean area derived through deep learning was sufficient for use in automatic weeding systems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.401-404
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• 2015

This paper proposes a high-performance in-loop filter in HEVC(High Efficiency Video Coding) encoder for Ultra HD video processing in real time. HEVC uses in-loop filter consisting of deblocking filter and SAO(Sample Adaptive Offset) to solve the problems of quantization error which causes image degradation. In the proposed in-loop filter encoder hardware architecture, the deblocking filter and SAO has a 2-level hybrid pipeline structure based on the $32{\times}32CTU$ to reduce the execution time. The deblocking filter is performed by 6-stage pipeline structure, and it supports minimization of memory access and simplification of reference memory structure using proposed efficient filtering order. Also The SAO is implemented by 2-statge pipeline for pixel classification and applying SAO parameters and it uses two three-layered parallel buffers to simplify pixel processing and reduce operation cycle. The proposed in-loop filter encoder architecture is designed by Verilog HDL, and implemented by 205K logic gates in TSMC 0.13um process. At 110MHz, the proposed in-loop filter encoder can support 4K Ultra HD video encoding at 30fps in realtime.

• Journal of The Korean Astronomical Society
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• v.53 no.5
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• pp.103-115
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• 2020

We analyze the spatially resolved kinematics of gas and stars for a sample of ten hidden type 1 AGNs in order to investigate the nature of their central sources and the scaling relation with host galaxy stellar velocity dispersion. We select our sample from a large number of hidden type 1 AGNs, which are identified based on the presence of a broad (full width at half maximum ≳1000 km s^-1) component in the Hα line profile and which are frequently mis-classified as type 2 AGNs because AGN continuum and broad emission lines are weak or obscured in the optical spectral range. We used the Blue Channel Spectrograph at the 6.5-m Multiple Mirror Telescope to obtain long-slit data with a spatial scale of 0.3 arcsec pixel^-1. We detected broad Hβ lines for only two targets; however, the presence of strong broad Hα lines indicates that the AGNs we selected are all low-luminosity type 1 AGNs. We measured the velocity, velocity dispersion, and flux of stellar continuum and gas emission lines (i.e., Hβ and [O III]) as a function of distance from the center. The spatially resolved gas kinematics traced by Hβ or [O III] are generally similar to the stellar kinematics except for the inner center, where signatures of gas outflows are detected. We compare the luminosity-weighted effective stellar velocity dispersions with the black hole masses and find that our hidden type 1 AGNs, which have relatively low back hole masses, follow the same scaling relation as reverberation-mapped type 1 AGN and more massive inactive galaxies.

• Journal of the Korean Society of Radiology
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• v.9 no.6
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• pp.403-408
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• 2015

Hard X-ray has been widely used in medical and industrial fields because it can be applied to observe the inside of a sample. Computed tomography provides sectional images of the sample through the reconstruction of the projection images. The quality of sectional images strongly depends on that of projection images. Ring artifact appeared on the seconal image can be made by the abnormal pixels of the detector used. In this study, we examine the ring artifact ratio in the circle phantom as a function of detection error of the detector used in computed tomography. The ring artifact increased with the increment of detection error under parallel and fan beam geometries and strongly increased near the center of rotation. The corrections, dead pixel and flat field corrections, for the images taken with the detector are required before the image reconstruction process to reduce the ring artifact in the computed tomography.