• Journal of Korean Ophthalmic Optics Society
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• v.7 no.1
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• pp.51-55
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• 2002

This study was to investigate the effect of EEG wave type of visual cortex on conjugate movement of eyeball according to movement of visual target. Visual evoked potential(VEP) system used the Bio-Pag(production in USA) and recorded to 586 computer. The illumination of test room was 50lux and the visual target was red light dot of 3cm size. The results of dextroversion and levoversion as follows : The visual stimulation waves on the visual cortex have about 71% of delta wave, about 12% of beta wave, about 9% theta wave and about 6% of alpha wave respectively. The dextroversion and levoversion state was similar results on the histogram amplitude of EEG wave, frequency of EEG wave type, EEG wave style and phase diagram of amplitude. Expecially the histogram amplitude of EEG wave appeared almost the Gaussian shape and the phase analysis of amplitude of EEG wave was nearly linear shape. On the fast fourier transform of the amplitude and Hz, the frequency was almost low frequency under 20 Hz, and the dextroversion and levoversion shape was similar results.

• Journal of Broadcast Engineering
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• v.22 no.1
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• pp.62-69
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• 2017

Accurate detection of traffic lights is very important for the advanced driver assistance system (ADAS). There have been many research developments in this area. However, conventional of image processing methods are usually sensitive to varying illumination conditions. This paper proposes a traffic light detection algorithm to overcome this situation. The proposed algorithm first detects the candidates of traffic light using the proposed color map and hue-saturation-value (HSV) Traffic lights are then detected using the conventional histogram of oriented gradients (HOG) descriptor and support vector machine (SVM). Finally, the proposed Multilayer HOG descriptor is used to determine the direction information indicated by traffic lights. The proposed algorithm shows a high detection rate in real-time.

• Korean Journal of Optics and Photonics
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• v.9 no.6
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• pp.362-367
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• 1998

Center Distance Finding (CDF) is a technique to find the sphere diameter by measuring the distance between two contacting spheres. The focal spots of the sphere clusters are formed in the back-focal plane by the transmission-mode optical microscope with the pseudothermal illumination source. Digital images taken by the CCD camera were processed by the software called Global Lab Image. The centers of the focal spots are found and the spot positions are expressed in terms of the CCD pixel elements, whose coordinate are calibrated by a heterodyne interferometer. The new CDF measurement system has been developed, which are more advantageous in time and convenience than the existing system, while the measurement uncertainly remains sufficient for its use as a magnification standard for optical microscopy. Two kinds of polystyrene spheres whose nominal diameters 3 and 10 $\mu\textrm{m}$ (NIST SRM 1962 and 1960) are measured with the uncertainly less than 1% at the confidence level of 99%, and the results are compared with the results of National Institute of Standards and Technology.

• Design & Manufacturing
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• v.14 no.3
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• pp.44-49
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• 2020

One of display trends today is development of high pixel density. To get high PPI, a small size of pixel must be developed. RGB pixel is arranged by evaporation process which determines pixel size. Normally, a fine metal mask (FMM; Invar alloy) has been used for evaporation process and it has advantages such as good strength, and low thermal expansion coefficient at low temperature. A FMM has been manufactured by chemical etching which has limitation to controlling the pattern shape and size. One of alternative method for patterning FMM is laser micromachining. Femtosecond laser is normally considered to improve those disadvantages for laser micromachining process due to such short pulse duration. In this paper, a femtosecond laser drilling for thickness of 16 ㎛ FMM is examined. Additionally, we introduce experimental results for controlling taper angle of hole by vibration module adapted in laser system. We used Ti:Sapphire based femtosecond laser with attenuating optics, co-axial illumination, vision system, 3-axis linear stage and vibration module. By controlling vibration amplitude, entrance and exit diameters are controllable. Using vibrating objective lens, we can control taper angle when femtosecond laser hole drilling by moving focusing point. The larger amplitude of vibration we control, the smaller taper angle will be carried out.

• Journal of Biomedical Engineering Research
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• v.27 no.3
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• pp.125-130
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• 2006

The number of the living endothelial cells and the shape of those are very import clinical parameters for the evaluation of the quality of cornea. In this paper, we developed the automated endothelial cell counting and shape analysis algorithm for a confocal microscope. Since, the endothelial images from the confocal microscope has a non-uniform illumination and low contrast between cell boundaries and cell bodies, it is very difficult to segment the cells from the endothelial images. To cope with these difficulties, we proposed the new two stage image processing algorithm. At first stage algorithm, we used a high-pass filter and histogram equalization to compensate the non-uniform brightness pattern and a morphological filter and a watershed method are applied to detect the boundary of cells. From this stage, we could count the number of cells in an endothelial image. At second stage algorithm, we used a Voronoi diagram method to classify the shape of cells. This cell shape analysis and the percent of hexagonal cells are very sensitive in detecting the early endothelium damage. To evaluate the performance of the proposed system, we p개cessed seven endothelial images obtained using a confocal microscope. The proposed system correctly counted 95.5% cells and classified 92.0% of hexagonal cell shapes. This result is better than any others in this research area.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.92-99
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• 2009

This paper established the range of the wavelength of traffic lights to detection the color of traffic lights and the color component segmentation with the range of the wavelength. Development of traffic light automatic discrimination system is consists of the color detection and the traffic lights recognition. In this thesis, it established the range of the wavelength of traffic lights to detection the color of traffic lights and the color segmentation with the range of the wavelength. By the segmentation, the traffic light colors(red, orange and green) can be detected and the background is changed into gray image. Next, we proposed the algorithm which can detect the area of traffic lights in the various surroundings with the wavelet transformation algorithm. Also, we proposed traffic lights recognition algorithm using between the edge operator and the Hausdorff distance algorithm based on CBIR(Content-based Image retrieval). Therefore, the proposed algorithm is more superior to the conventional algorithm by experimenting with the illumination including the traffic lights and the backgrounds with various images.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.3
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• pp.22-28
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• 2007

The STIR(Signal Tracking & Illumination Radar) in KDX(Korean Destroyer Experimental) combat system acquires target from designating 3-D target information of surveillance radar (MW-08), and The performance of radar is decided by target acquisition time and accuracy of tracking loop because the STIR tracks automatically in accordance with tracking algorithm. In the view of ship, elements related with target acquisition time of the STIR can be various. In this paper the target acquisition time of the STIR is reduced by identifying the elements and suggesting the performance improvement method. The way of performance improvement is suggested through analysing main affecting factors. First, tracking algorism is required for analysis. Second, fitness of parameters that control elements related with acquisition distance is analyzed. And the third, accuracy of ship based sensors is analyzed. In conclusion, acquisition time against ship target can be advanced to 3 seconds from 10 seconds.

• Journal of IKEEE
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• v.24 no.1
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• pp.147-153
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• 2020

Conventional lane detection algorithms have problems in that the detection rate is lowered in road environments having a large change in curvature and illumination. The probabilistic Hough transform method has low lane detection rate since it exploits edges and restrictive angles. On the other hand, the method using a sliding window can detect a curved lane as the lane is detected by dividing the image into windows. However, the detection rate of this method is affected by road slopes because it uses affine transformation. In order to detect lanes robustly and avoid obstacles, we propose driving assist system using semantic segmentation based on deep learning. The architecture for segmentation is SegNet based on VGG-16. The semantic image segmentation feature can be used to calculate safety space and predict collisions so that we control a vehicle using adaptive-MPC to avoid objects and keep lanes. Simulation results with CARLA show that the proposed algorithm detects lanes robustly and avoids unknown obstacles in front of vehicle.

• Journal of Sensor Science and Technology
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• v.5 no.3
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• pp.65-73
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• 1996

One of the important factor in drug stuffs to a patient is to inject exact amount with stable flow rates. Since improper injection amount and flow rates would cause bad effect to recovery of a patient, the detecting sensors with high sensitivity is required for an injection pump systems' performance improvement. In this study, the three sensors, piezo film sensor, photo transistor and photo array, were compared to find best one for an injection pump monitoring system. Using suggested data processing technique and photo array sensors, we could minimize the effect of interference, disturbance, illumination, and sensitivity change caused by sensor's position. According to the experiments, the photo array showed the higher reliance than any other the three types of sensors.

• Journal of Biosystems Engineering
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• v.27 no.2
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• pp.151-160
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• 2002

Cow image processing technique would be useful not only for recognizing an individual but also for establishing the image database and analyzing the shape of cows. A cow (Holstein) has usually the unique speckle pattern. In this study, the individual recognition of cow was carried out using the speckle pattern and the content-based image retrieval technique. Sixty cow images of 16 heads were captured under outdoor illumination, which were complicated images due to shadow, obstacles and walking posture of cow. Sixteen images were selected as the reference image for each cow and 44 query images were used for evaluating the efficiency of individual recognition by matching to each reference image. Run-lengths and positions of runs across speckle area were calculated from 40 horizontal line profiles for ROI (region of interest) in a cow body image after 3 passes of 5$\times$5 median filtering. A similarity measure for recognizing cow individuals was calculated using Euclidean distance of normalized G-frame histogram (GH). normalized speckle run-length (BRL), normalized x and y positions (BRX, BRY) of speckle runs. This study evaluated the efficiency of individual recognition of cow using Recall(Success rate) and AVRR(Average rank of relevant images). Success rate of individual recognition was 100% when GH, BRL, BRX and BRY were used as image query indices. It was concluded that the histogram as global property and the information of speckle runs as local properties were good image features for individual recognition and the developed system of individual recognition was reliable.