• The KIPS Transactions:PartC
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• v.13C no.1 s.104
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• pp.19-26
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• 2006

Recently, web server hacking is trending toward web application hacking which uses comparatively vulnerable web applications based on open sources. And, it is possible to hack databases using web interfaces because web servers are usually connected databases. Web application attacks use vulnerabilities not in web server itself, but in web application structure, logical error and code error. It is difficult to defend web applications from various attacks by only using pattern matching detection method and code modification. In this paper, we propose a method to secure the web applications based on profiling which can detect and filter out abnormal web application requests.

• Journal of IKEEE
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• v.25 no.2
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• pp.243-251
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• 2021

In this paper, we propose a measurement technique of indoor location based on markerless applicable to AR. The proposed technique has the following originality. The first is to extract feature points and use them to generate local patches to enable faster computation by learning and using only local patches that are more useful than the surroundings without learning the entire image. Second, learning is performed through deep learning using the convolution neural network structure to improve accuracy by reducing the error rate. Third, unlike the existing feature point matching technique, it enables indoor location measurement including left and right movement. Fourth, since the indoor location is newly measured every frame, errors occurring in the front side during movement are prevented from accumulating. Therefore, it has the advantage that the error between the final arrival point and the predicted indoor location does not increase even if the moving distance increases. As a result of the experiment conducted to evaluate the time required and accuracy of the measurement technique of indoor location based on markerless applicable to AR proposed in this paper, the difference between the actual indoor location and the measured indoor location is an average of 12.8cm and a maximum of 21.2cm. As measured, the indoor location measurement accuracy was better than that of the existing IEEE paper. In addition, it was determined that it was possible to measure the user's indoor location in real time by displaying the measured result at 20 frames per second.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.29-34
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• 2002

Fingerprint recognition technology was studied by classification and matching. In general, there are five different classifications left loop, right loop, whore, arch, and tented-arch. These classifications are used to determine which class an individual's fingerprint belong to, thereby identifying the individual's fingerprint pattern. The result of this classification, which is sent to the large fingerprint database as an index, helps reduce the matching time and enhance the accuracy of fingerprint matching. The existing fingerprint classification method relies on the number and location of cores and delta points called singular points. The drawback of this method is the lack of accuracy stemming from the classification difficulty involving unclear and/or partially-erased fingerprints. The current paper presents an efficient classification method to rectify the problem associated with identifying Singular points from unclear fingerprints. This method, which is based on Gabor filter's unique characteristics for magnifying directional patterns and frequency range selections, improves fingerprint classification accuracy significantly. In this paper, this method is described and its test result is presented for verification.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.57-74
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• 2022

Recently, artificial intelligence parking control systems have increased the recognition rate of vehicle license plates using deep learning, but there is a problem that they cannot determine vehicles with fake license plates. Despite these security problems, several institutions have been using the existing system so far. For example, in an experiment using a counterfeit license plate, there are cases of successful entry into major government agencies. This paper proposes an improved system over the existing artificial intelligence parking control system to prevent vehicles with such fake license plates from entering. The proposed method is to use the degree of matching of the front feature points of the vehicle as a passing criterion using the ORB algorithm that extracts information on feature points characterized by an image, just as the existing system uses the matching of vehicle license plates as a passing criterion. In addition, a procedure for checking whether a vehicle exists inside was included in the proposed system to prevent the entry of the same type of vehicle with a fake license plate. As a result of the experiment, it showed the improved performance in identifying vehicles with fake license plates compared to the existing system. These results confirmed that the methods proposed in this paper could be applied to the existing parking control system while taking the flow of the original artificial intelligence parking control system to prevent vehicles with fake license plates from entering.

• Journal of Korea Game Society
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• v.11 no.4
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• pp.143-149
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• 2011

This paper presents a novel camera tracking method based on model with multiple planes. The proposed algorithm detects QR code that is one of the most popular types of two-dimensional barcodes. A 3D model is imported from the detected QR code for augmented reality application. Based on the geometric property of the model, the vertices are detected and tracked using optical flow. A clipping algorithm is applied to identify each plane from model surfaces. The proposed method estimates the homography from coplanar feature correspondences, which is used to obtain the initial camera motion parameters. After deriving a linear equation from many feature points on the model and their 3D information, we employ DLT(Direct Linear Transform) to compute camera information. In the final step, the error of camera poses in every frame are minimized with local Bundle Adjustment algorithm in real-time.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.168-175
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• 2013

Color consistency in stereoscopic contents is important for 3D display systems. Even with a stereo camera of the same model and with the same hardware settings, complex color discrepancies occur when acquiring high quality stereo images. In this paper, we propose an integrated color matching method that use cumulative histogram in global matching and estimated 3D-distance for the stage of local matching. The distance between the current pixel and the target local region is computed using depth information and the spatial distance in the 2D image plane. The 3D-distance is then used to determine the similarity between the current pixel and the target local region. The overall algorithm is described as follow; First, the cumulative histogram matching is introduced for reducing global color discrepancies. Then, the proposed local color matching is established for reducing local discrepancies. Finally, a weight-based combination of global and local matching is computed. Experimental results show the proposed algorithm has improved global and local error correction performance for stereoscopic contents with respect to other approaches.

• Journal of the Korea Society of Computer and Information
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• v.15 no.11
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• pp.91-99
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• 2010

Recently, recognizing user resource for personalized service has been needed in digital content service fields. Especially, to analyze user taste, recommend music and service music related information need recognition of user music file in case of online music service. Music related information service is offered through recognizing user music based on tag information. Recognition error has grown by weak points like changing and removing of tag information. Techniques of content based user music recognition with music signal itself are researched for solving upper problems. In this paper, we propose user music recognition on the internet by extracted feature from music signal. Features are extracted after suitable preprocessing for structure of content based user music recognition. Recognizing on music server consist of feature form are progressed with extracted feature. Through this, user music can be recognized independently of tag data. 600 music was collected and converted to each 5 music qualities for proving of proposed recognition. Converted 3000 experiment music on this method is used for recognition experiment on music server including 300,000 music. Average of recognition ratio was 85%. Weak points of tag based music recognition were overcome through proposed content based music recognition. Recognition performance of proposed method show a possibility that can be adapt to online music service in practice.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.50-53
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• 2022

Recently, there have been cases in which counterfeit foreign ships have entered and left domestic ports several times. Vessels have a ship-specific serial number given by the International Maritime Organization (IMO) to identify the vessel, and IMO marking is mandatory on all ships built since 2004. In the case of airports and ports, which are representative logistics platforms, a security system is essential, but it is difficult to establish a security system at a port and there are many blind spots, which can cause security problems due to insufficient security systems. In this paper, a port security system is designed using deep learning object recognition and OpenCV. The security system process extracts the IMO number of the ship after recognizing the object when entering the ship, determines whether it is the same ship through feature point matching for ships with entry records, and stores the ship image and IMO number in the entry/exit DB for the first arrival vessel. Through the system of this paper, port security can be strengthened by improving the efficiency and system of port logistics by increasing the efficiency of port management personnel and reducing incidental costs caused by unauthorized entry.

• Journal of Korean Society of Rural Planning
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• v.24 no.1
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• pp.47-60
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• 2018

계획적이고 안정적인 영농을 위해 영농작업 인력을 확보하는 것은 매우 중요하다. 하지만 농가인구의 감소로 인한 농업인력 확보의 어려움과 농업노동 임금의 지속적인 증가는 경영주에게 이중의 고통이 되고 있다. 따라서 본 연구에서는 농가처분가능소득이 전국에서 가장 높은 강원도를 지역 표집으로 선정하여 Bivariate Probit 모형을 이용해 내국인과 외국인 고용의 상호 관계를 고려한 고용인력 수요 결정요인을 살펴보았다. 분석결과, 첫째, 3개월 이상 노동력을 고용하는 농가들의 경우 내국인 고용수요와 외국인 고용수요 간에는 양(+)의 상관관계가 있는 것으로 나타났다. 둘째, 전형적인 도시근교 농업의 특징을 나타내는 춘천시에 비해 강원도내 타 지역 농가들은 다른 변수들이 일정할 경우 내국인과 외국인의 고용수요가 증가하는 것으로 나타났다. 셋째, 젊은 경영주일수록 내국인 상시 고용에 대한 수요가 높고, 농가조직에 참여하고 있는 농가일수록 자가노동 확률은 0.13% 감소하고, 상시 농업 노동력에 대한 수요가 증가하는 것으로 나타났다. 이러한 분석결과를 종합한 농업 노동력 확보를 위한 정책적 시사점으로는 첫째, 상시고용된 농업인력들을 대상으로 국내외 문화 차이를 인지하고, 내국인 노동자와 외국인 노동자간의 협력 네트워크 구축을 위한 영농교육 확대가 필요하다. 둘째, 각 지역별로 내국인 또는 외국인 노동자의 상시고용 수요가 상이한 것으로 나타나 강원도내 지역별 농산업 현황을 기반으로 "(가칭)강원도 농업 인력 수급 플랫폼" 구축이 필요하다. 셋째, 청년창업농과 농가조직 참여 농가들을 대상으로 농작업 상시고용 인력을 우선적으로 매칭해 주는 것이 필요하다.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.8
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• pp.98-103
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• 2019

A more accurate method of feature point extraction and matching for three-dimensional reconstruction using low-resolution images of crops is proposed herein. This method is important in basic computer vision. In addition to three-dimensional reconstruction from exact matching, map-making and camera location information such as simultaneous localization and mapping can be calculated. The results of this study suggest applicable methods for low-resolution images that produce accurate results. This is expected to contribute to a system that measures crop growth condition.