• Convergence Security Journal
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• v.13 no.3
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• pp.9-15
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• 2013

Calculating of matching cost is an important for efficient stereo matching. To investigate the performance of matching process, the concepts of the existing methods are introduced. Also we analyze the performance and merits of them. The simplest matching costs assume constant intensities at matching image locations. We consider matching cost functions which can be distinguished between pixel-based and window-based approaches. The Pixel-based approach includes absolute differences (AD) and sampling-intensitive absolute differences (BT). The window-based approach includes the sum of the absolute differences, the sum of squared differences, the normalized cross-correlation, zero-mean normalized cross-correlation, census transform, and the absolute differences census transform (AD-Census). We evaluate matching cost functions in terms of accuracy and time complexity. In terms of the accuracy, AD-Census method shows the lowest matching error ratio (the best solution). The ZNCC method shows the lowest matching error ratio in non-occlusion and all evaluation part. But it performs high matching error ratio at the discontinuities evaluation part due to blurring effect in the boundary. The pixel-based AD method shows a low complexity in terms of time complexity.

• ALGAE
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• v.19 no.2
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• pp.129-137
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• 2004

Since cultural eutrophication has the detrimental effects on estuarine and coastal ecosystems, recognition of early stage of nutrient over-enrichment is critical for effective managements of the ecosystems. Since released nutrients into coastal ecosystems are diluted and dissipated through tidal action and rapid uptakes by marine plants, monitoring of in situ nutrient concentrations may not be useful for detecting early eutrophication on coastal and estuarine ecosystems. To develop an effective indicator of cultural eutrophication using marine plants, tissue N content and area normalized leaf mass of eelgrass, Zostera marina were examined in Kosung Bay and Koje Bay on the south coast of Korea from June 2001 to April 2003. Eelgrass tissue N content exhibited obvious seasonal variations. Leaf N content was highest during winter and early spring and lowest during summer. Eelgrass tissue N content was higher at Kosung Bay site, which has higher sediment organic content, than at Koje Bay site. Area normalized leaf mass showed reverse trend of leaf N content, and consequently, eelgrass leaf N content and leaf mass exhibited strong negative correlation at both study sites. The results of the present study suggested that the ratio of eelgrass leaf N content to area normalized leaf mass can be applied to assess environmental nitrogen conditions on the coastal and estuarine ecosystems.

• Bulletin of the Korean Chemical Society
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• v.28 no.9
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• pp.1472-1476
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• 2007

Artificial neural networks (ANNs) are successfully developed for the modeling and prediction of normalized polarity parameter (ETN) of 216 various solvents with diverse chemical structures using a quantitative-structure property relationship. ANN with architecture 5-9-1 is generated using five molecular descriptors appearing in the multi-parameter linear regression (MLR) model. The most positive charge of a hydrogen atom (q+), total charge in molecule (qt), molecular volume of solvent (Vm), dipole moment (μ) and polarizability term (πI) are input descriptors and its output is ETN. It is found that properly selected and trained neural network with 192 solvents could fairly represent the dependence of normalized polarity parameter on molecular descriptors. For evaluation of the predictive power of the generated ANN, an optimized network is applied for prediction of the ETN values of 24 solvents in the prediction set, which are not used in the optimization procedure. Correlation coefficient (R) and root mean square error (RMSE) of 0.903 and 0.0887 for prediction set by MLR model should be compared with the values of 0.985 and 0.0375 by ANN model. These improvements are due to the fact that the ETN of solvents shows non-linear correlations with the molecular descriptors.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.709-720
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• 2017

In this study, we tried to analyze the correlation between corn yield and, satellite-based vegetation index, NDVI (Normalized Difference Vegetation Index) and various climatic factors in the three provinces of Northeast China during the past 20 years (1996-2015). The corn yields in the corn cultivation area of all three provinces showed a statistically significant positive correlation with the NDVI of the harvest period. Also, these have significant negative correlation with the daily maximum temperature in August and September and the occurrence frequency of above $30^{\circ}C$ for the summer season. The correlation between the corn yields and the precipitation showed a significant positive coefficient in only Liaoning Province in July, but the correlation was not found in Jilin and Heilongjiang Provinces. In this study, the NDVI and the daily maximum temperature data are suitable to be used as predictors of corn yield in the three provinces of Northeast China provinces.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.2
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• pp.148-161
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• 2015

The examples that used camera in the vehicle is increasing with the growth of the automotive market, and the importance of the image processing technique is expanding. In particular, the Lane Departure Warning System (LDWS) and related technologies are under development in various fields. In this paper, in order to improve the lane recognition rate more than the conventional method, we extract a Normalized Luminance Descriptor value and a Normalized Contrast Descriptor value, and adjust image gamma values to modulate Normalized Image Quality by using the correlation between the extracted two values. Then, we apply the Hough transform using the optimized accumulator cells to the four-channel ROI. The proposed algorithm was verified in 27 frame/sec and $640{\times}480$ resolution. As a result, Lane recognition rate was higher than the average 97% in day, night, and late-night road environments. The proposed method also shows successful lane recognition in sections with curves or many lane boundary.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.555-562
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• 2012

This paper presents a hybrid method for improving the recognition performance, which is based on the nonlinear histogram equalization, features extraction, and statistical correlation of images. The nonlinear histogram equalization based on a logistic function is applied to adaptively improve the quality by adjusting the brightness of the image according to its intensity level frequency. The statistical correlation that is measured by the normalized cross-correlation(NCC) coefficient, is applied to rapidly and accurately express the similarity between the images. The local features based on independent component analysis(ICA) that is used to calculate the NCC, is also applied to statistically measure the correct similarity in each images. The proposed method has been applied to the problem for recognizing the 30-face images of 40*50 pixels. The experimental results show that the proposed method has a superior recognition performances to the method without performing the preprocessing, or the methods of conventional and adaptively modified histogram equalization, respectively.

• Journal of Korea Water Resources Association
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• v.53 no.5
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• pp.337-345
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• 2020

In order to provide information for proper management of groundwater resources, an analysis of the effects of precipitation and groundwater withdrawal on groundwater levels is needed. In this study, we analyzed the correlation of precipitation-groundwater level and groundwater withdrawal-groundwater level using time series data converted by normalized standard deviation (Nor.St.Dev) and cross correlation coefficient (CCC) for nine groundwater monitoring wells in the middle mountainous area in the southeastern Jeju Island. First, the CCCs of precipitation-groundwater level were estimated using daily time series data, and the low CCCs of up to 0.3 were obtained. However, the result of using the Nor.St.Dev showed a clearer correlation by obtaining a CCC of up to 0.8. In addition, in most cases, precipitation variability and groundwater level variability had positive CCCs, whereas groundwater withdrawal variability and groundwater level variability had negative CCCs. Therefore, the groundwater level in this study area was largely influenced by precipitation with little effect of groundwater withdrawal. Lastly, as a result of analyzing the relative effects of Seongpanak and Gyorae rainfall station on the groundwater level, the rainfall at the relatively downstream Gyorae rainfall station has more influence. The analysis method used in this study can be easily used for analyzing the effects of precipitation and groundwater withdrawal on groundwater level variability in other regions in the future.

• Composites Research
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• v.29 no.1
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• pp.1-6
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• 2016

Low-speed impact was localized on a stiffened composite structure, using 4 FBG sensors with 100 kHz-sampling rate interrogator and devised localization algorithm. The composite specimen consists of a main spar and several stringers, and the overall size of the specimen's surface is about $0.8{\times}1.2m$. Pre-stored reference data for 247 grid locations and 36 stiffener locations are gathered and used as comparison target for a random impact signal. The proposed algorithm uses the normalized cross-correlation method to compare the similarities of the two signals; the correlation results for each sensor's signal are multiplied by others, enabling mutual compensation. 20 verification points were successfully localized with a maximum error of 43.4 mm and an average error of 17.0 mm. For the same experimental setup, the performance of the proposed method is evaluated by reducing the number of sensors. It is revealed that the mutual compensation between the sensors is most effective in the case of a two sensor combination. For the sensor combination of FBG #1 and #2, the maximum localization error was 42.5 mm, with average error of 17.4 mm.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.473-479
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• 2019

This study applied SGM (Semi Global Matching) to generate DSM (Digital Surface Model) using WorldView-1 high-resolution satellite stereo pair in Terrassa, Spain provided by ISPRS (International Society for Photogrammetry and Remote Sensing). The SGM is an image matching algorithm that performs the computation of the matching cost for the stereo pair in multi-paths and aggregates the computed costs sequentially. This method finally calculates the disparity corresponding to the minimum (or maximum) value of the aggregation cost. The cost was applied to MI (Mutual Information), NCC (Normalized Cross-Correlation), and CT (Census Transform) in order to the SGM. The accuracy and performance of the outline representation result in DSM by each cost are presented. Based on the images used and the subject area, the accuracy of the CT cost results was the highest, and the outline representation was also most clearly depicted. In addition, while the SGM method represented more detailed outlines than the existing software, many errors occurred in the water area.

• Journal of Biosystems Engineering
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• v.33 no.5
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• pp.348-354
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• 2008

Egg grading is determined by exterior and interior quality. Among the evaluation methods for the egg quality, a candling method is common to identify eggs with cracked shells and interior defects. But this method is time-consuming and laborious. In addition, practically, it is challenging to detect hairline and micro cracks. In this study, an on-line inspection system based on acoustic resonance frequency analysis was developed to detect hairline cracks on eggshells. A roller conveyor was used to transfer eggs along one lane to the impact position where each of eggs rotated by the roller was excited with an impact device at four different locations on the eggshell equator. The impact device was consisted of a plastic hammer and a rotary solenoid. The acoustic response of the egg to the impact was measured with a small condenser microphone at the same position as the impact device was installed. Two acoustic parameters, correlation coefficient for normalized power spectra and standard deviation of peak resonant frequencies, were used to detect cracked eggs. Intact eggs showed relatively high correlations among the four normalized power spectra and low standard deviations of the four peak resonant frequencies. On the other hand, cracked eggs showed low correlations and high standard deviations as compared to the intact. This method allowed a crack detection rate of 97.6%.