• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2271-2280
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• 1999

In this paper, a variable motion estimation scheme based on HBMA(Hierarchical Block Matching Algorithm) to improve the performance and to reduce heavy computational and transmission load, is presented. The proposed algorithm is composed of four steps. First, block activity for each block is defined using the edge information of differential image between two sequential images, and then average block activity of the present image is found by taking the mean of block activity. Secondly, camera pan compensation is carried out, according to the average activity of the image, in the hierarchical pyramid structure constructed by wavelet transform. Next, the LUT classifying each block into one among Moving, No Moving, Semi-Moving Block according to the block activity compensated camera pan is obtained. Finally, as varying the block size and adaptively selecting the initial search layer and the search range referring to LUT, the proposed variable HBMA can effectively carries out fast motion estimation in the hierarchical pyramid structure. The cost function needed above-mentioned each step is only the block activity defined by the edge information of the differential image in the sequential images.

• The Korean Journal of Pesticide Science
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• v.17 no.3
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• pp.155-161
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• 2013

The residue patterns of clothianidin and thiacloprid, insecticides registered in the ginseng, were investigated to predict pre-harvest residues limits (PHRL). Pesticides were treated under Korea GAP (Good Agricultural Practices) with the recommended dose (single dose) and twice of recommended dose (double dose). Samples were collected 11 times over 42 days (each 0, 2, 5, 8, 12, 16, 20, 24, 28, 33, 42 days after treatment). Residues of clothinidin and thiacloprid were analyzed by UPLC/TQD. Biological half-life of clothinidin in single dose and double dose were 14.6 days and 10.2 days and that of thiacloprid were also 9.7 days and 11.2 days, respectively. The PHRL of ginseng on 10 days before harvest was 0.3 mg/kg in clothianidin and 0.18 mg/kg in thiacloprid.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.4
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• pp.87-98
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• 2011

Detecting a moving object from videos and tracking it are basic and necessary preprocessing steps in many video systems like object recognition, context aware, and intelligent visual surveillance. In this paper, we propose a method that is able to detect a moving object quickly and accurately in a condition that background and light change in a real time. Furthermore, our system detects strongly an object in a condition that the target object is covered with other objects. For effective detection, effective Eigen-space and FCM are combined and employed, and a CONDENSATION algorithm is used to trace a detected object strongly. First, training data collected from a background image are linear-transformed using Principal Component Analysis (PCA). Second, an Eigen-background is organized from selected principal components having excellent discrimination ability on an object and a background. Next, an object is detected with FCM that uses a convolution result of the Eigen-vector of previous steps and the input image. Finally, an object is tracked by using coordinates of an detected object as an input value of condensation algorithm. Images including various moving objects in a same time are collected and used as training data to realize our system that is able to be adapted to change of light and background in a fixed camera. The result of test shows that the proposed method detects an object strongly in a condition having a change of light and a background, and partial movement of an object.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.786-792
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• 2010

This paper presents a real-time lane detection method which can accurately find the lane-mark boundaries in complex road environment. Unlike many existing methods that pay much attention on the post-processing stage to fit lane-mark position among a great deal of outliers, the proposed method aims at removing those outliers as much as possible at feature extraction stage, so that the searching space at post-processing stage can be greatly reduced. To achieve this goal, a grid-based morphology operation is firstly used to generate the regions of interest (ROI) dynamically, in which a directional edge-linking algorithm with directional edge-gap closing is proposed to link edge-pixels into edge-links which lie in the valid directions, these directional edge-links are then grouped into pairs by checking the valid lane-mark width at certain height of the image. Finally, lane-mark colors are checked inside edge-link pairs in the YUV color space, and lane-mark types are estimated employing a Bayesian probability model. Experimental results show that the proposed method is effective in identifying lane-mark edges among heavy clutter edges in complex road environment, and the whole algorithm can achieve an accuracy rate around 92% at an average speed of 10ms/frame at the image size of $320{\times}240$.

• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.409-418
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• 2021

Conformal coating is a technology that protects PCB(Printed Circuit Board) and minimizes PCB failures. Since the defects in the coating are linked to failure of the PCB, the coating surface is examined for air bubbles to satisfy the successful conditions of the conformal coating. In this paper, we propose an algorithm for detecting problematic bubbles in high-risk groups by applying image signal processing. The algorithm consists of finding candidates for problematic bubbles and verifying candidates. Bubbles do not appear in visible light images, but can be visually distinguished from UV(Ultra Violet) light sources. In particular the center of the problematic bubble is dark in brightness and the border is high in brightness. In the paper, these brightness characteristics are called valley and mountain features, and the areas where both characteristics appear at the same time are candidates for problematic bubbles. However, it is necessary to verify candidates because there may be candidates who are not bubbles. In the candidate verification phase, we used convolutional neural network models, and ResNet performed best compared to other models. The algorithms presented in this paper showed the performance of precision 0.805, recall 0.763, and f1-score 0.767, and these results show sufficient potential for bubble test automation.

• The Korean Journal of Applied Statistics
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• v.21 no.2
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• pp.233-245
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• 2008

In this work, a new adaptive weighted mean filter is proposed for preserving image details while effectively suppressing impulse noise. The proposed filter is based on a noise pixel detection-estimation strategy. All the pixels are first detected using an impulse noise detector. Then the detected noise pixels are replaced with the output of the weighted mean filter over adaptive working window according to the rate of corrupted neighborhood pixels, while noise-free pixels are left unaltered. We compare the proposed filter to other existing filters in the qualitative measure and quantitative measures such as PSNR and MAE as well as computation time to verify the capability of the proposed filter. Extensive simulations show that the proposed filter performs better than other filters in impulse noise suppression and detail preservation without increasing of running time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.6A
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• pp.577-582
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• 2008

In this paper, we present a scheme to overcome the worst case complexity of the sphere decoder. If the number of visited nodes reaches the threshold, the detected symbol vector is determined between two candidate symbol vectors. One candidate symbol vector is obtained from the demodulated output of ZF receiver which is initial stage of the sphere decoder. The other candidate symbol vector consists of two sub-symbol vectors. The first sub-symbol vector consists of lately visited nodes running from the most upper layer. The second one contains corresponding demodulated outputs of ZF receiver. Between these two candidate symbol vectors, the one with smaller euclidean distance to the received symbol vector is chosen as detected symbol vector. In addition, we show the upper bound of symbol error rate performance for the sphere decoder using the proposed scheme. In the simulation, the proposed scheme shows the significant reduction of the worst case complexity while having negligible SER performance degradation.

• Korean Journal of Food Science and Technology
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• v.16 no.4
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• pp.383-387
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• 1984

The difference of glycoalkaloids content on various parts of May Queen and Irish Cobbler potatoes was determined. ${\alpha}-Chaconine$ and ${\alpha}-Solanine$ were isolated from the glycoalkaloids by use of high performance liquid chromatography. It was found that the 99% of the total glycoalkaloids was existent in cortex part of all varieties. Glycoalkaloids content was higher in apical or basal part than the middle part. ${\alpha}-Chaconine$ content of the cortex showed no differences among parts of the potato in both varieties. ${\alpha}-Solanine$ was not detected in medulla part. The potatoes were classified into 4 groups depending on the weight and the glycoalkaloids content of the middle part. As the weight of the potato decreased the glycoalkaloids content of cortex part increased. Glycoalkaloids content was lower in medulla part and no constant tendency was observed.

• Journal of IKEEE
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• v.27 no.3
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• pp.345-349
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• 2023

In this paper, we propose a study on the development of deep learning structure for defective pixel detection of next-generation smart LED display board using imaging device. In this research, a technique utilizing imaging devices and deep learning is introduced to automatically detect defects in outdoor LED billboards. Through this approach, the effective management of LED billboards and the resolution of various errors and issues are aimed. The research process consists of three stages. Firstly, the planarized image data of the billboard is processed through calibration to completely remove the background and undergo necessary preprocessing to generate a training dataset. Secondly, the generated dataset is employed to train an object recognition network. This network is composed of a Backbone and a Head. The Backbone employs CSP-Darknet to extract feature maps, while the Head utilizes extracted feature maps as the basis for object detection. Throughout this process, the network is adjusted to align the Confidence score and Intersection over Union (IoU) error, sustaining continuous learning. In the third stage, the created model is employed to automatically detect defective pixels on actual outdoor LED billboards. The proposed method, applied in this paper, yielded results from accredited measurement experiments that achieved 100% detection of defective pixels on real LED billboards. This confirms the improved efficiency in managing and maintaining LED billboards. Such research findings are anticipated to bring about a revolutionary advancement in the management of LED billboards.

• Korean Journal of Environmental Agriculture
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• v.21 no.2
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• pp.149-155
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• 2002

Two pesticides commonly used for lettuce cultivation including chlorpyrifos and procymidone were subjected to a field residue trial to ensure safety of terminal residues in the harvest. After pesticides were applied at standard and double rates in a foliar spray, leaf persistence of their residues was investigated far 10 days prior to harvest. Even though far exceeded the tolerances, initial leaf residues were rapidly dissipated with time and remained only 0.4$\sim$7.2% of the residues in the harvest. As well fitted by the first-order kinetics, biological half-lives of the pesticide residues in lettuce leaves ranged 1.2$\sim$2.6 days. Slow dissipation of the residues in the harvest was observed during storage at room temperature and 4$^{\circ}C$ for 7 days. Portions of dislodgeable residues which resided in detergent washings decreased as time elapsed. Patterns in dissipation and distribution of dislodgeable residues were not largely affected by the application rate of pesticides. It is concluded that timing of pesticide application, that is, pre-harvest interval would be the first factor to determine the terminal residue level in edible portions of lettuce.