• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.163-177
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• 2024

The fingerprint image quality relies on the clearness of separated ridges by valleys and the uniformity of the separation. The condition of skin still dominate the overall quality of the fingerprint. However, the identification performance of such system is very sensitive to the quality of the captured fingerprint image. Fingerprint image quality analysis and enhancement are useful in improving the performance of fingerprint identification systems. A fuzzy technique is introduced in this paper for both fingerprint image quality analysis and enhancement. First, the quality analysis is performed by extracting four features from a fingerprint image which are the local clarity score (LCS), global clarity score (GCS), ridge_valley thickness ratio (RVTR), and the Global Contrast Factor (GCF). A fuzzy logic technique that uses Mamdani fuzzy rule model is designed. The fuzzy inference system is able to analyse and determinate the fingerprint image type (oily, dry or neutral) based on the extracted feature values and the fuzzy inference rules. The percentages of the test fuzzy inference system for each type is as follow: For dry fingerprint the percentage is 81.33, for oily the percentage is 54.75, and for neutral the percentage is 68.48. Secondly, a fuzzy morphology is applied to enhance the dry and oily fingerprint images. The fuzzy morphology method improves the quality of a fingerprint image, thus improving the performance of the fingerprint identification system significantly. All experimental work which was done for both quality analysis and image enhancement was done using the DB_ITS_2009 database which is a private database collected by the department of electrical engineering, institute of technology Sepuluh Nopember Surabaya, Indonesia. The performance evaluation was done using the Feature Similarity index (FSIM). Where the FSIM is an image quality assessment (IQA) metric, which uses computational models to measure the image quality consistently with subjective evaluations. The new proposed system outperformed the classical system by 900% for the dry fingerprint images and 14% for the oily fingerprint images.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.4
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• pp.437-444
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• 2020

A lunar rover's optical camera is used to provide navigation and terrain information in an exploration zone. However, due to the scant presence of atmosphere, the Moon has homogeneous terrain with dark soil. Also, in extreme environments, the rover has limited data storage with low computation capability. Thus, for successful exploration, it is required to examine feature detection and matching methods which are robust to lunar terrain and environmental characteristics. In this research, SIFT, SURF, BRISK, ORB, and AKAZE are comparatively analyzed with lunar terrain images from a lunar rover. Experimental results show that SIFT and AKAZE are most robust for lunar terrain characteristics. AKAZE detects less quantity of feature points than SIFT, but feature points are detected and matched with high precision and the least computational cost. AKAZE is adequate for fast and accurate navigation information. Although SIFT has the highest computational cost, the largest quantity of feature points are stably detected and matched. The rover periodically sends terrain images to Earth. Thus, SIFT is suitable for global 3D terrain map construction in that a large amount of terrain images can be processed on Earth. Study results are expected to provide a guideline to utilize feature detection and matching methods for future lunar exploration rovers.

• Journal of Korea Multimedia Society
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• v.8 no.10
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• pp.1369-1382
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• 2005

Vehicle segmentation, which extracts vehicle areas from road scenes, is one of the fundamental opera tions in lots of application areas including Intelligent Transportation Systems, and so on. We present a vehicle segmentation approach for still images captured from outdoor CCD cameras mounted on the supporting poles. We first divided the input image into a set of two-dimensional grids and then calculate the feature values of the edges for each grid. Through analyzing the feature values statistically, we can find the optimal rectangular grid area of the vehicle. Our preprocessing process calculates the statistics values for the feature values from background images captured under various circumstances. For a car image, we compare its feature values to the statistics values of the background images to finally decide whether the grid belongs to the vehicle area or not. We use dynamic programming technique to find the optimal rectangular gird area from these candidate grids. Based on the statistics analysis and global search techniques, our method is more systematic compared to the previous methods which usually rely on a kind of heuristics. Additionally, the statistics analysis achieves high reliability against noises and errors due to brightness changes, camera tremors, etc. Our prototype implementation performs the vehicle segmentation in average 0.150 second for each of $1280\times960$ car images. It shows $97.03\%$ of strictly successful cases from 270 images with various kinds of noises.

• Atmosphere
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• v.18 no.2
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• pp.97-109
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• 2008

The aerosol characteristics in terms of 4 different cases (Asian dust, fog, clear sky and cloud) which had happened at Anmyeon Island in April 2006 were studied using various measurements such as the Micro Pulse Lidar (MPL), sunphotometer, $\beta$-ray $PM_{10}$ Analyzer, anemoscope and anemometer. In addition, synoptic charts, back trajectory analyses and satellite images were also used to help characterize the aerosol events. The aerosol optical properties were featured by the Aerosol Optical Depth (AOD) and ${\AA}ngstr\ddot{o}m$ exponent which were estimated by the sunphotometer. When Anmyeon Island was dominated by the Asian dust, the AOD was sharply increased as seven times as a yearly average of it (0.35). As compared with a yearly average of the ${\AA}ngstr\ddot{o}m$ exponent of 0.97, the ${\AA}ngstr\ddot{o}m$ exponent of a dust day was significantly low (0.099). In addition, $PM_{10}$ mass concentration showed an extremely high record. The maximum concentration reached $1790.5{\mu}gm^{-3}$ on 8 April 2006. The maximum mass concentration was shown with delay when the wind speed of $0ms^{-1}$ was observed. It was also found that a satellite image of the MODIS-RGB had a good agreement with the results of those measurements. It was shown that the MPL was able to describe effectively the vertical distribution of aerosol for all the cases. In particular, the MPL evidently captured the aerosol layer before the cloud observation. The aerosol layer was similarly described by the AOD. On a clear sky day, the AOD had not only a very low value (0.054) but also a feature of homogeneity.

• Asia Marketing Journal
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• v.13 no.4
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• pp.253-264
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• 2012

A growing number of Korean companies are trying to expand their business area into global market due to saturation in the Korean domestic market. Home shopping industry arriving on mature stage is faced with less growth recently. CJ O Shopping which is a top ranked home shopping company in Korea, has been showing meaningful performances by earlier moving to global market with thorough preparations. CJ O Shopping's global marketing strategy focused on asian countries including China, India, Vietnam, and Japan is going successfully, which enables top ranked on-line retailing company in asia as well as in Korea. CJ O Shopping effectively penetrated into overseas market with both core competence based on Korean home shopping model and rigorous preliminary study on target market. Especially shoppertainment (Shopping+Entertainment) that is unique feature of globally competitive Korean home shopping created huge differentiations in target market. Also choosing the influential local partner, sharing the business goals, and building the joint venture could make stable operations, thereby easily earning of well-established awareness from target consumers. A step ahead entry of competitors and intensive localization of CJ O Shopping's core competence for arriving safe in target market were additional key factors for global marketing success. We can extract above key factors for success as implications of case study on CJ O Shopping's global marketing, and expect those factors to be spread into lots of Korean companies and utilized as successful strategies for global marketing.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.163-170
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• 2019

Over the past decade, the development of the Web explosively increased the data. Feature selection step is an important step in extracting valuable data from a large amount of data. This study proposes a novel opinion mining model based on combining feature selection (FS) methods with Word embedding to vector (Word2vec) and BOW (Bag-of-words). FS methods adopted for this study are CFS (Correlation based FS) and IG (Information Gain). To select an optimal FS method, a number of classifiers ranging from LR (logistic regression), NN (neural network), NBN (naive Bayesian network) to RF (random forest), RS (random subspace), ST (stacking). Empirical results with electronics and kitchen datasets showed that LR and ST classifiers combined with IG applied to BOW features yield best performance in opinion mining. Results with laptop and restaurant datasets revealed that the RF classifier using IG applied to Word2vec features represents best performance in opinion mining.

• Information Systems Review
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• v.24 no.1
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• pp.1-19
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• 2022

Social media-based communication has become crucial part of our personal and official lives. Therefore, it is no surprise that social media sentiment analysis has emerged an important way of detecting potential customers' sentiment trends for all kinds of companies. However, social media sentiment analysis suffers from huge number of sentiment features obtained in the process of conducting the sentiment analysis. In this sense, this study proposes a novel method by using Bayesian Network. In this model MBFS (Markov Blanket-based Feature Selection) is used to reduce the number of sentiment features. To show the validity of our proposed model, we utilized online review data from Yelp, a famous social media about restaurant, bars, beauty salons evaluation and recommendation. We used a number of benchmarking feature selection methods like correlation-based feature selection, information gain, and gain ratio. A number of machine learning classifiers were also used for our validation tasks, like TAN, NBN, Sons & Spouses BN (Bayesian Network), Augmented Markov Blanket. Furthermore, we conducted Bayesian Network-based what-if analysis to see how the knowledge map between target node and related explanatory nodes could yield meaningful glimpse into what is going on in sentiments underlying the target dataset.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.10
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• pp.1991-2000
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• 1994

In this paper, an alagorithm with six types of classification is suggested for the recognition system of hand-written Korean characters. After thinning process and truncating process for noise redection. The input images are used generalized by $64\times64$ size. The six type classification is composed of preliminary and secondary classification process by using the learning algoritm of multi-layer perceptron. Subblock Hough transform is used as local feature and sampling Hough transform is used as global feature. Experiment is conducted for 1800 characters which is written 31 times per each type by 10 persons. The 90% recognition rate is resulted by the preliminary classification of detection the final consonant and by the secondary classification of detecting the vowels.

• The Research Journal of the Costume Culture
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• v.21 no.3
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• pp.309-323
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• 2013

This study examined the expression mode and feature about photomontage indicated in the 21st century's Contemporary fashion. This intends to have better understanding on photomontage and to provide theoretical explanation to help a creative design development using photomontage in the future. For the research method, review over photomontage concept and its historical background was carried out with relevant literature and precedent studies. Then, analysis was followed about 258 pieces of photomontage application works featured in the four major global collections from 2001S/S to 2011F/W. Among types of photomontage expression in the Contemporary fashion, objects in the nature like animal, plant, scenery picture took up the highest frequency as motive. Other types appeared in the following order: the people-oriented type such as eminent person's figure or partial body, the ready-made image including diverse daily goods in the modern consumption society, a variety of printed stuff like cartoon, newspaper and magazine, the type of photomontage expression through borrowing the earlier famous art pieces or doing the cooperative work with artists in different fields, applications like architecture, land marks in many cities in the world, and interior, things assembled with various images, modified religious images in photomontage from Buddha or holy picture. Therefore, the modern fashion that uses photomontage could possibly feature popularity, naturalism, playfulness and creativity.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.4
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• pp.33-42
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• 2013

This paper describes a multiple vehicle tracking algorithm using an integrated probabilistic data association filter (IPDAF) in urban environments. The algorithm consists of two parts; a pre-processing stage and an IPDA tracker. In the pre-processing stage, measurements are generated by a feature extraction method that manipulates raw data into predefined geometric features of vehicles as lines and boxes. After that, the measurements are divided into two different objects, dynamic and static objects, by using information of ego-vehicle motion. The IPDA tracker estimates not only states of tracks but also existence probability recursively. The existence probability greatly assists reliable initiation and termination of track in cluttered environment. The algorithm was validated by using experimental data which is collected in urban environment by using single laser scanner.