• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.12-21
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• 2006

In this paper, we propose a technique for extracting attentive objects in images using feature maps, regardless of the complexity of images and the position of objects. The proposed method uses feature maps with edge and color information in order to extract attentive objects. We also propose a reference map which is created by integrating feature maps. In order to create a reference map, feature maps which represent visually attentive regions in images are constructed. Three feature maps including edge map, CbCr map and H map are utilized. These maps contain the information about boundary regions by the difference of intensity or colors. Then the combination map which represents the meaningful boundary is created by integrating the reference map and feature maps. Since the combination map simply represents the boundary of objects we extract the candidate object regions including meaningful boundaries from the combination map. In order to extract candidate object regions, we use the convex hull algorithm. By applying a segmentation algorithm to the area of candidate regions to separate object regions and background regions, real object regions are extracted from the candidate object regions. Experiment results show that the proposed method extracts the attentive regions and attentive objects efficiently, with 84.3% Precision rate and 81.3% recall rate.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.1 s.307
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• pp.55-66
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• 2006

We propose a progressive image retrieval method based on an efficient combination of multiresolution color and torture features in wavelet transform domain. As a color feature, color autocorrelogram of the hue and saturation components is chosen. As texture features, BDIP and BVLC moments of the value component are chosen. For the selected features, we obtain multiresolution feature vectors which are extracted from all decomposition levels in wavelet domain. The multiresolution feature vectors of the color and texture features are efficiently combined by the normalization depending on their dimensions and standard deviation vector, respectively, vector components of the features are efficiently quantized in consideration of their storage space, and computational complexity in similarity computation is reduced by using progressive retrieval strategy. Experimental results show that the proposed method yields average $15\%$ better performance in precision vs. recall and average 0.2 in ANMRR than the methods using color histogram color autocorrelogram SCD, CSD, wavelet moments, EHD, BDIP and BVLC moments, and combination of color histogram and wavelet moments, respectively. Specially, the proposed method shows an excellent performance over the other methods in image DBs contained images of various resolutions.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.187-195
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• 2013

Most of former studies for car license plate detection restrict the image acquisition environment. The aim of this research is to diminish the restrictions by proposing a new method of using SIFT and neural network. SIFT can be used in diverse situations with less restriction because it provides size- and rotation-invariance and large discriminating power. SIFT extracted from the license plate image is divided into the internal(inside class) and the external(outside class) ones and the classifier is trained using them. In the proposed method, by just putting the various types of license plates, the trained neural network classifier can process all of the types. Although the classification performance is not high, the inside class appears densely over the plate region and sparsely over the non-plate regions. These characteristics create a local feature map, from which we can identify the location with the global maximum value as a candidate of license plate region. We collected image database with much less restriction than the conventional researches. The experiment and evaluation were done using this database. In terms of classification accuracy of SIFT keypoints, the correct recognition rate was 97.1%. The precision rate was 62.0% and recall rate was 50.2%. In terms of license plate detection rate, the correct recognition rate was 98.6%.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.155-160
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• 2014

There are many image processing based algorithms and applications that fail when illumination change occurs. Therefore, the illumination change has to be detected then the illumination change occurred images need to be enhanced in order to keep the appropriate algorithm processing in a reality. In this paper, a new method for detecting illumination changes efficiently in a real time by using local region information and fuzzy logic is introduced. The effective way for detecting illumination changes in lighting area and the edge of the area was selected to analyze the mean and variance of the histogram of each area and to reflect the changing trends on previous frame's mean and variance for each area of the histogram. The ways are used as an input. The changes of mean and variance make different patterns w hen illumination change occurs. Fuzzy rules were defined based on the patterns of the input for detecting illumination changes. Proposed method was tested with different dataset through the evaluation metrics; in particular, the specificity, recall and precision showed high rates. An automatic parameter selection method was proposed for contrast limited adaptive histogram equalization method by using entropy of image through adaptive neural fuzzy inference system. The results showed that the contrast of images could be enhanced. The proposed algorithm is robust to detect global illumination change, and it is also computationally efficient in real applications.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.3
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• pp.161-166
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• 2017

In recent times, many people have problems of nutritional imbalance; lack or surplus intake of a specific nutrient despite the variety of available foods. Accordingly, the interest in health and diet issues has increased leading to the emergence of various mobile applications. However, most mobile applications only record the user's diet history and show simple statistics and usually provide only general information for healthy diet. It is necessary for users interested in healthy eating to be provided recommendation services reflecting their food interest and providing customized information. Hence, we propose a menu recommendation method which includes calculating the recommended calorie amount based on the user's physical and activity profile to assign to each food group a substitution unit. In addition, our method also analyzes the user's food preferences using food intake history. Thus it satisfies recommended intake unit for each food group by exchanging the user's preferred foods. Also, the excellence of our proposed algorithm is demonstrated through the calculation of precision, recall, health index and the harmonic average of the 3 aforementioned measures. We compare it to another method which considers user's interest and recommended substitution unit. The proposed method provides menu recommendation reflecting interest and personalized health status by which user can improve and maintain a healthy dietary habit.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2006.04a
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• pp.166-170
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• 2006

본 연구에서는 폐광산 주변에 산재되어 있는 광미/광폐석을 처리하기 위하여 고형화 실증 실험을 수행하였다. 고형화 공정에서 흔히 사용하는 포틀랜드 시멘트와 MSG-E, MSG-N을 고화제로 사용하였으며 현장 광미 및 광폐석을 대상으로 고화체를 양생하고 고화체의 압축강도 및 중금속 용출 정도를 측정하였다. 고화체의 물리/화학적 특성을 비교하기 위해 광미/고화제 비율, 배합수/고화제 비율 그리고 고화체 양생기간을 실험인자로 설정하였다. 실험 결과 광미/고화제의 비율 1:1 만을 고려하더라도 중금속 용출의 급격한 감소가 이루어지는 것을 확인할 수 있었으며 광미/고화제의 비율을 3:1 이하로 유지시키는 경우, 고화체의 압축강도가 현행 폐기물 관리법(20조 관련)에서 규정하고 있는 차단형 매립시설 내부막의 압축강도 기준인 $0.21kgf/mm^2$ 보다 높은 것으로 나타났다. 다양한 pH를 갖는 수용액에 대하여 시간에 따른 고화체의 중금속 용출률을 측정한 결과, 수용액의 pH가 1과 13인 강산/강염기 용액에서 일부 중금속의 용출 농도가 지하수 생활용수 기준치를 초과하였으나, pH와 3 - 11인 경우에는 중금속 용출률이 급격히 감소하여 모두 기준치 이하를 나타내었다. 또한, pH가 1과 13인 수용액의 경우에도 고화체와 반응하는 시간이 증가할수록 고화체의 buffering 효과에 의해 수용액의 pH가 감소하였다. 이러한 결과는 현장에서 접촉수의 pH가 강산이나 강염기라 하여도, 고화체의 buffering 효과에 의해 시간이 지남에 따라 수용액의 pH가 낮아져 고화체로부터의 중금속 용출은 매우 감소할 것임을 의미한다.ss of an active application defined using the model. The technique is developed in a platform- and language-independent way, and it is algorithmic and can be automated by computer program. We give an example dealing with network auction to illustrate the use of the model and the verification technique.품으로 내부 온도분포를 측정하였으며, 유한차분법 프로그램으로 대류열전달계수를 결정하였다. 대류열전달계수는 792에서 2,107 W/m$^2$로 분석되었다. 대류열전달 계수는 액상식품과의 상대속도가 증가함에 따라서 증가하였고, 점도가 증가함에 따라서는 감소하였다.ce of precision/recall of 90.99%/92.52%, and 93.39%/93.41% respectively. 의한 변성에 부분적으로 보호 작용을 나타 낼 것으로 추정된다.경(製麴72時間頃)의 활성(活性)은 보리쌀국(麴), 밀가루국(麴), 찹쌀국(麴), 고구마국(麴)의 순이었다.험 결과 오전용 사료는 관행적인 산란계 배합사료에서 Ca공급제를 제외한 것을 급여하고, 오후용 사료는 Ca공급제를 3배 첨가한 T2처리로 15:00~16:00시에 교체급여를 하면 사료섭취량 감소와 사료비 절감면에서 바람직할 것으로 사료되며, 고에너지-고단백질-저Ca의 분말사료와 저에너지-저단백질-고Ca의 펠렛사료를 혼합급여하면 산란계의 사료

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.353-361
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• 2020

Due to the rapid urbanization, various traffic problems such as traffic jams during commute and regular traffic jams are occurring. In order to solve these traffic problems, it is necessary to quickly and accurately estimate and analyze traffic volume. ITS (Intelligent Transportation System) is a system that performs optimal traffic management by utilizing the latest ICT (Information and Communications Technology) technologies, and research has been conducted to analyze fast and accurate traffic volume through various techniques. In this study, we proposed a deep learning-based vehicle detection method using UAV (Unmanned Aerial Vehicle) video for real-time traffic analysis with high accuracy. The UAV was used to photograph orthogonal videos necessary for training and verification at intersections where various vehicles pass and trained vehicles by classifying them into sedan, truck, and bus. The experiment on UAV dataset was carried out using YOLOv3 (You Only Look Once V3), a deep learning-based object detection technique, and the experiments achieved the overall object detection rate of 90.21%, precision of 95.10% and the recall of 85.79%.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.49-57
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• 2013

A novel approach for the feature selection is proposed, which is the important preprocessing task of on-line document classification. In previous researches, the features based on information from their single population for feature selection task have been selected. In this paper, a mixed feature set is constructed by selecting features from multi-population as well as single population based on various information. The mixed feature set consists of two feature sets: the original feature set that is made up of words on documents and the transformed feature set that is made up of features generated by LSA. The hybrid feature selection method using both filter and wrapper method is used to obtain optimal features set from the mixed feature set. We performed classification experiments using the obtained optimal feature sets. As a result of the experiments, our expectation that our approach makes better performance of classification is verified, which is over 90% accuracy. In particular, it is confirmed that our approach has over 90% recall and precision that have a low deviation between categories.

• The Journal of the Korea Contents Association
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• v.12 no.2
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• pp.40-51
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• 2012

Recently, many users discuss and argue with others using replying comments. This implies that a series of comments can be a new source of information since various opinions can be appeared in the dispute. It is important to understand the implicit dispute structure immanent in the comment set. In this paper, we examine the characteristics of disputes using replying comments in the Internet forum sites using a set of test articles with the comments collected from SketicalLeft and Agora, which are famous Internet forum sites in Korea. And we propose a new method for detecting and visualizing the dispute sections and relations from a large set of replying comments. To show the performance of our method, we measured precision, recall, and F-measure. According to the experimental results, the F-measures of the detection of the comments in dispute are about 0.84 (SketpcialLeft) and 0.83 (Agora); those of the detection of the commenter pairs in dispute are 0.75 (SketpcialLeft) and 0.82 (Agora), respectively. Since our method exploits the temporal order of commenters to detect the disputes, it is not dependent on the host language nor on the typos in comments. Also, our method can help the readers to grasp the structure of controversy hidden in the comment set through the visualized view.

• The Journal of Society for e-Business Studies
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• v.21 no.3
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• pp.15-28
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• 2016

This paper proposes a system recommending spatial information what user wants with collecting and analyzing tweets around the user's location by using the GPS information acquired in mobile. This system has built an emotion dictionary and then derive the recommendation score of morphological analyzed tweets to provide not just simple information but recommendation through the emotion analysis information. The system also calculates distance between the recommended tweets and user's latitude-longitude coordinates and the results showed the close order. This paper evaluates the result of the emotion analysis in a total of 10 areas with two keyword 'Restaurants' and 'Performance.' In the result, the number of tweets containing the words positive or negative are 122 of the total 210. In addition, 65 tweets classified as positive or negative by analyzing emotions after a morphological analysis and only 46 tweets contained the meaning of the positive or negative actually. This result shows the system detected tweets containing the emotional element with recall of 38% and performed emotion analysis with precision of 71%.