• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.410-413
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• 2009

Wafer pre-alignment is to find the center and the orientation of a wafer and to move the wafer to the desired position and orientation. In this paper, an area camera based pre-aligning method is presented that captures 8 wafer images regularly during 360 degrees rotation. From the images, wafer edge positions are extracted and used to estimate the wafer's center and orientation using least square circle fitting. These information are utilized for the proper alignment of the wafer.

• Journal of Food Hygiene and Safety
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• v.38 no.3
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• pp.123-130
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• 2023

Salmonella spp. are prevalent foodborne pathogens that are infective at relatively low concentrations, thus posing a serious health threat, especially to young children and the elderly. In several countries, the management and regulation of Salmonella spp. in food, including seafood, adhere to a negative detection standard. The risk of infection is particularly high when seafood is consumed raw, which underscores the importance of timely detection of pathogenic microorganisms, such as Salmonella. Accordingly, this study aimed to develop a combined pre-treatment and detection method that includes pre-culture and DNA extraction in order to detect five species of Salmonella at concentrations below 10 CFU/mL in seafood. The effectiveness of the proposed method was assessed in terms of the composition of the enrichment (pre-culture) medium, minimum incubation time, and minimum cell concentration for pathogen detection. Furthermore, a practical DNA extraction method capable of effectively handling high salt conditions was tested and found to be successful. Through polymerase chain reaction, Salmonella spp. Were detected and positively identified in shellfish samples at cell concentrations below 10 CFU/g. Thus, the proposed method, combining sample pre-treatment and cell culture with DNA extraction, was shown to be an effective strategy for detecting low cellular concentrations of harmful bacteria. The proposed methodology is suitable as an economical and practical in situ pre-treatment for effective detection of Salmonella spp. in seafood.

• Journal of Environmental Health Sciences
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• v.22 no.1
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• pp.36-44
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• 1996

A comparison was made of two detection methods(UV absorbence detection and fluorescence detection with pre-column derivatization, with trifluoroacetic acid) coupled with HPLC for the simultaneous determination of aflatoxin $B_1, B_2, G_1$ and $G_2$. A good separation of the four aflatoxins was achieved on a reversed-phase $C_{18}$ column (30 cm x 3.9 mm) with methanol-acetonitrile-water(20+20+60) for absorbence detection or acetonitrile-water(25+75) for fluorescence detection at the flow rate of 1.0 ml/min. The calibration graphs were linear over the ranges 100 ppb-1 ppm for $B_1/G_1$ and 30~300 ppb for $B_2/G_1$ with absorbence detection, and 1~500 ppb for $B_1/G_1$ and 0.3~150 ppb for $B_2/G_2$ with fluorescence detection. The correlation coefficients were greater than 0.94 and 0.99 for absorbance detection and for fluorescence detection, respectively. The detection limit was 100 ng for $B_1/G_1$ and 30 ng for $B_2/G_2$ with absorbence detection, and 1 ng for $B_1/G_1$ and 0.3 ng for $B_2/G_2$ with fluorescence detection. Recovery rates of aflatoxin $B_1, B_2, G_1$ and $G_2$ added to yeast-extract sucrose broth medium were 66.6%, 59.4%, 67.5% and 59.2%, respectively, for absorbence detection and 82.9%, 71.5%, 80.0% and 69.3%, respectively, for fluorescence detection. The four aflatoxins in culture medium were quantitatively detected by the two methods. The aflatoxins in the rice sample were not detected the absorbence detection method, but were below 10 ppb using the fluorescence detection method. Analysis of aflatoxins by both the absorbence and fluorescence methods coupled with HPLC showed acceptable linearity and good recovery. The absorbence detection was less timeconsuming and safer for treatment. The fluorescence detection was more elective and sensitive though elevated $B_1$ and $G_1$ contents were determined from the TFA-induced conversion of $B_1$ to $B_{2a}$ and $G_1$ to $G_{2a}$.

• Journal of Korea Multimedia Society
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• v.18 no.12
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• pp.1519-1527
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• 2015

TFT-LCD automatic defect inspection system for detecting defects in place of the visual tester does pre-processing, candidate defect pixel detection, and recognition and classification through a blob analysis. An over-detection result of defects acts as an undue burden of blob analysis for recognition and classification. In this paper, we propose defect detection method based on the histogram distribution modeling of TFT-LCD image to minimize over-detection of candidate defective pixels. Primary defect candidate pixels are detected estimating the skewness of the luminance distribution histogram of the background pixels. Based on the detected defect pixels, the defective pixels other than noise pixels are detected using the distribution histogram model of the local area. Experimental results confirm that the proposed method shows an excellent defect detection result on the image containing the various types of defects and the reduction of the degree of over-detection as well.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.10C
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• pp.983-991
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• 2005

Human faces are commonly found in a video such as a drama and provide useful information for video content analysis. Therefore, face detection plays an important role in applications such as face recognition, and face image database management. In this paper, we propose a face detection algorithm based on pre-processing of scene change detection for indexing and cast searching in video. The proposed algorithm consists of three stages: scene change detection stage, face region detection stage, and eyes and mouth detection stage. Experimental results show that the proposed algorithm can detect faces successfully over a wide range of facial variations in scale, rotation, pose, and position, and the performance is improved by $24\%$with profile images comparing with conventional methods using color components.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.158-158
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• 2023

Characterizing the performance of precipitation (hereafter PRE) products in estimating the uncertainties in daily PRE in the era of global warming is of great value to the ecosystem's sustainability and human survival. This study intercompares the performance of different PRE products (gauge-based, satellite and reanalysis) sourced from the Frequent Rainfall Observations on GridS (FROGS) database over diverse climate zones in Africa and identifies regions where they depict minimal uncertainties in order to build optimal maps as a guide for different climate users. This is achieved by utilizing various techniques, including the triple collection (TC) approach, to assess the capabilities and limitations of different PRE products over nine climatic zones over the continent. For daily scale analysis, the uncertainties in light PRE (0.1 5mm/day) are prevalent over most regions in Africa during the study duration (2001-2016). Estimating the occurrence of extreme PRE events based on daily PRE 90th percentile suggests that extreme PRE is mainly detected over central Africa (CAF) region and some coastal regions of west Africa (WAF) where the majority of uncorrected satellite products show good agreement. The detection of PRE days and non-PRE days based on categorical statistics suggests that a perfect POD/FAR score is unattainable irrespective of the product type. Daily PRE uncertainties determined based on quantitative metrics show that consistent, satisfactory performance is demonstrated by the IMERG products (uncorrected), ARCv2, CHIRPSv2, 3B42v7.0 and PERSIANN_CDRv1r1 (corrected), and GPCC, CPC_v1.0, and REGEN_ALL (gauge) during the study period. The optimal maps that show the classification of products in regions where they depict reliable performance can be recommended for various usage for different stakeholders.

• Proceedings of the Acoustical Society of Korea Conference
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• 1993.06a
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• pp.259-262
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• 1993

In this paper, a new pitch beginning point detection method by extracting the G-peak, is proposed. By the speech production model, the area of the first peak on a pitch interval of speech signals is emphasized. By using the above characteristics, this method have more advantages than the others for pitch beginning point detection. The defective decision caused by an impulsive noise is minimized and the pre-filtering is not necessary for this method, because the integration of signals takes place in the process.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.687-693
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• 2006

Image co-registration is the process of overlaying two images of the same scene, one of which represents a reference image, while the other is geometrically transformed to the one. In order to improve efficiency and effectiveness of the co-registration approach, the author proposed a pre-qualified area matching algorithm which is composed of feature extraction with canny operator and area matching algorithm with cross correlation coefficient. For refining matching points, outlier detection using studentized residual was used and iteratively removes outliers at the level of three standard deviation. Throughout the pre-qualification and the refining processes, the computation time was significantly improved and the registration accuracy is enhanced. A prototype of the proposed algorithm was implemented and the performance test of 3 Landsat images of Korea. showed: (1) average RMSE error of the approach was 0.435 pixel; (2) the average number of matching points was over 25,573; (3) the average processing time was 4.2 min per image with a regular workstation equipped with a 3 GHz Intel Pentium 4 CPU and 1 Gbytes Ram. The proposed approach achieved robustness, full automation, and time efficiency.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.3
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• pp.15-19
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• 2006

In shallow water active sonar environment, reverberation which is a non-white noise is one of the main source of performance degradation of target detection. In this case, the received signal is whitened before applying matched filter known as an optimum filter in the presence of white noise. However implementation of this method is very difficult because of the non-stationary characteristic of reverberation. Traditionally reverberation is assumed local stationary. In this paper, we estimate a range of stationary of reverberation signal, and then propose a pre-whitening method which improve the performance of pre-whitening block normalized matched filter in presence of non-white reverberation noise. Proposed whitener shows better whitening performance than traditional whitener because it use later as well as before reverberation of target signal. To evaluate performance of the proposed whitener, an actual measurement data sampled at the East-Sea is used for computer simulation. The target detector with new whitener is shown better performance than detector with traditional whitener.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.40-47
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• 2009

A motion adaptive video noise reduction scheme is proposed by cascading a temporal filter and a spatial filter. After a noise-robust motion detection is performed with a pre-spatial filter, the strength of the motion adaptive temporal filter is controlled by the amount of temporal movement. In order to fully utilize the temporal correlation of video signal, noisy input image is processed first by the temporal filter, therefore, image details of temporally stationary region are quite well preserved while undesired noises are suppressed. In contrast to the pre-spatial filter used for the robust motion detection, the cascaded post-spatial filter removes the remained noises by considering the strength of the temporal filter and the spatial self-similarity search results obtained from the pre-spatial filter.