• Title/Summary/Keyword: Police Image

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Extraction of core and delta Points in Fingerprint (지문에서 코아와 델타의 추출)

  • Jeong, Yang-Kwon
    • The Journal of the Acoustical Society of Korea
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    • v.13 no.1
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    • pp.42-48
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    • 1994
  • Recently pictorial information processing has become increasingly important So, this paper described that feature points of fingerprint used to recognize fingerprints for identification in a government or arresting criminals in an institution like a police station related to crime. We apply an algorithm based on minimization of fuzzy theory to thinning and then the image into a certain size of squares. We have got some information about cores and deltas from the data encoding Into one of the eight directional codes. We could extract about $80\%$ feature points as the result of the experiment.

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Comparison of Deep-Learning Algorithms for the Detection of Railroad Pedestrians

  • Fang, Ziyu;Kim, Pyeoungkee
    • Journal of information and communication convergence engineering
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    • v.18 no.1
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    • pp.28-32
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    • 2020
  • Railway transportation is the main land-based transportation in most countries. Accordingly, railway-transportation safety has always been a key issue for many researchers. Railway pedestrian accidents are the main reasons of railway-transportation casualties. In this study, we conduct experiments to determine which of the latest convolutional neural network models and algorithms are appropriate to build pedestrian railroad accident prevention systems. When a drone cruises over a pre-specified path and altitude, the real-time status around the rail is recorded, following which the image information is transmitted back to the server in time. Subsequently, the images are analyzed to determine whether pedestrians are present around the railroads, and a speed-deceleration order is immediately sent to the train driver, resulting in a reduction of the instances of pedestrian railroad accidents. This is the first part of an envisioned drone-based intelligent security system. This system can effectively address the problem of insufficient manual police force.

Study on the Security Officials in the Study of the Working Environment and Education (경호공무원의 근무환경과 교육에 관한 연구)

  • Jo, Sung-Gu;Kim, Dong-Je;Choi, Jong-Gwang;Park, Ju-Hyeon
    • Korean Security Journal
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    • no.37
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    • pp.247-268
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    • 2013
  • Country is security agencies with the launch of the Park Chung Hee government president security service act was enacted since installed successfully now undergoing a large-scale international events reborn professional Security agencies, including the North and the Northeast, but the conflict continues because of the national reduce the threat to the security without a destination. However countermeasures against these threats is emphasized, but in an effort to raise the country is security officials security agencies working environment and training for these studies have not performed in this study was started. In order to achieve this purpose, president security service and the seoul police agency personnel working in the field for 45 people who were interviewed, recently developed by utilizing Nvivo 8 program to improve working conditions in the analysis of organizational culture 51(78.46%), Image 7(10.93%), physical and mental 6(9.37%) were categorized, educational institutions in the direction of a police constable 56(76.71%), educational psychology 12(16.43%), theory of education 5(6.84%) were categorized as high. We look at the research results suggest that the authority of the president security service president security service officials in tissue culture officials were struggling to belong to an organization, you need to induce a change in culture has been raised, the current president of the Security Service, as well as specialized police constable training within the organization establish the necessary institutions respectively.

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A Study on Development of Systems to Enforce the interfering Cars on the Ramp (끼어들기 단속시스템 개발 연구)

  • Lee, Ho-Won;Hyun, Cheol-Seung;Joo, Doo-Hwan;Jeong, Jun-Ha;Lee, Choul-Ki
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.11 no.5
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    • pp.7-14
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    • 2012
  • We frequently confront with cars interfering into our lane on the ramp. We suffered from serious traffic congestion due to the interfering cars. But the police enforcement has not done actively because it's hard to enforce. In this study, we have evaluated the systems to enforce cutting-in cars through the field test. Generally, the image processing method depends on the weather. To overcome this limitation we proposed a new algorithm combined with section detection method. In the filed test we concluded the results as follows. Whereas the violation detection rate of the general image processing was 58.2%, a new algorithm proposed by this study was 74.5%. And, an error rate enforcing vehicles that do not violate was 0.0%. Also, we can use the existing facilities, such as street light because of compact and lightweight systems which are integrated camera with controller. Therefore, we concluded that it is possible to enforce the interfering Cars using vehicle enforcement systems.

A pilot application study of densitometric image analysis as a potential comparative evaluation method for visualized fingerprints

  • Kim, Eun-Ji;Kim, Soo-Kyung;Seo, Kyung-Suk;Choi, Sung-Woon
    • Analytical Science and Technology
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    • v.33 no.4
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    • pp.197-207
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    • 2020
  • The current comparison methods with scoring systems that are used to compare visualized latent fingerprints (LF) have disadvantages. Evaluators using these methods are prone to make errors and fail to discriminate LFs correctly to notice the differences among those LFs. Therefore, a comparative and quantitative evaluation method that is capable of obtaining more objective and quantitative results is needed. Densitometric image analysis (DIA) is used in other fields as a reliable semi-quantitative comparison method. To apply DIA to LFs, the potential variables that can occur during the DIA process were tested. The visualized ridges of LFs can be compared using the concentration of dots against the background to make it possible to analyze the ridges with DIA. The variables that can be present during the DIA process include the thickness of the analysis line, the number of ridges to be taken, the number of divided zones within each of the fingerprints, and the angles of the analysis line against the ridge lines that were selected. From the analysis of the inked fingerprints and circular lines that are similar to fingerprints, the angle of the analysis lines with the ridge line was the most significant variable. The preliminary test result was applied to the comparison of LFs that were developed with the powder method and then compared with the AFIS analysis. A similar trend was found, and a more detailed and semi-quantitative comparison of the visualized LFs was possible. In the future, it is necessary to check the evaluative ability of the DIA method by analyzing the visualized LFs with other various development methods. However, DIA is currently an option that can be used as an objective comparative evaluation method during fingerprint studies with supplementary role.

Distortion Invariant Vehicle License Plate Extraction and Recognition Algorithm (왜곡 불변 차량 번호판 검출 및 인식 알고리즘)

  • Kim, Jin-Ho
    • The Journal of the Korea Contents Association
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    • v.11 no.3
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    • pp.1-8
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    • 2011
  • Automatic vehicle license plate recognition technology is widely used in gate control and parking control of vehicles, and police enforcement of illegal vehicles. However inherent geometric information of the license plate can be transformed in the vehicle images due to the slant and the sunlight or lighting environment. In this paper, a distortion invariant vehicle license plate extraction and recognition algorithm is proposed. First, a binary image reserving clean character strokes can be achieved by using a DoG filter. A plate area can be extracted by using the location of consecutive digit numbers that reserves distortion invariant characteristic. License plate is recognized by using neural networks after geometric distortion correction and image enhancement. The simulation results of the proposed algorithm show that the accuracy is 98.4% and the average speed is 0.05 seconds in the recognition of 6,200 vehicle images that are obtained by using commercial LPR system.

A Study on the Trigger Technology for Vehicle Occupant Detection (차량 탑승 인원 감지를 위한 트리거 기술에 관한 연구)

  • Lee, Dongjin;Lee, Jiwon;Jang, Jongwook;Jang, Sungjin
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.120-122
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    • 2021
  • Currently, as demand for cars at home and abroad increases, the number of vehicles is decreasing and the number of vehicles is increasing. This is the main cause of the traffic jam. To solve this problem, it operates a high-ocompancy vehicle (HOV) lane, a multi-passenger vehicle, but many people ignore the conditions of use and use it illegally. Since the police visually judge and crack down on such illegal activities, the accuracy of the crackdown is low and inefficient. In this paper, we propose a system design that enables more efficient detection using imaging techniques using computer vision to solve such problems. By improving the existing vehicle detection method that was studied, the trigger was set in the image so that the detection object can be selected and the image analysis can be conducted intensively on the target. Using the YOLO model, a deep learning object recognition model, we propose a method to utilize the shift amount of the center point rather than judging by the bounding box in the image to obtain real-time object detection and accurate signals.

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Escape Route Prediction and Tracking System using Artificial Intelligence (인공지능을 활용한 도주경로 예측 및 추적 시스템)

  • Yang, Bum-suk;Park, Dea-woo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.225-227
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    • 2022
  • Now In Seoul, about 75,000 CCTVs are installed in 25 district offices. Each ward office in Seoul has built a control center for CCTV control and is building information such as people, vehicle types, license plate recognition and color classification into big data through 24-hour artificial intelligence intelligent image analysis. Seoul Metropolitan Government has signed MOUs with the Ministry of Land, Infrastructure and Transport, the National Police Agency, the Fire Service, the Ministry of Justice, and the military base to enable rapid response to emergency/emergency situations. In other words, we are building a smart city that is safe and can prevent disasters by providing CCTV images of each ward office. In this paper, the CCTV image is designed to extract the characteristics of the vehicle and personnel when an incident occurs through artificial intelligence, and based on this, predict the escape route and enable continuous tracking. It is designed so that the AI automatically selects and displays the CCTV image of the route. It is designed to expand the smart city integration platform by providing image information and extracted information to the adjacent ward office when the escape route of a person or vehicle related to an incident is expected to an area other than the relevant jurisdiction. This paper will contribute as basic data to the development of smart city integrated platform research.

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A Comprehensive Review of the Foreign Literature regarding Protest Crowd Counting (집회시위 참가인원 집계방식에 대한 선행연구 고찰 - 국외연구 분석 중심으로 -)

  • Kim, Hak-kyong
    • Korean Security Journal
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    • no.58
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    • pp.9-34
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    • 2019
  • The Korean Police Force is equipped with the dual responsibility to not only protect the constitutional right to protest, but also prevent potential disorder and misconduct might be caused by the abuse of such a right. To this end, the Korean national police employ the crowd counting methodology, termed 'Maximum Figure at Any One Time' with a view to dispatching the proportionate number of police officers to protest scenes for safety management. However, protest organizers rather take advantage of 'Cumulative Figure' methodology, the purpose of which being to publicize the wide recognition of success, noticeably by demonstrating that as many people as possible support for their cause or voice. Hence, different estimates generated by different methods have raised serious political issues in Korean society. Nevertheless, it is found out that there are only three existing academic studies in Korea regarding crowd counting methods, and they are mainly geared towards comparing the two methods, unfortunately without any attempt to analyze the foreign literature in details. Keeping the research gap in mind, the research conducts a comprehensive review of the foreign literature with relation to protest crowd counting methods. Derived from the review and analysis, the counting methods can be broadly categorized into the three models such as: 1) Grid/Density Model, 2) Moving Crowds Model, and 3) Electronic & Non-Image Model. In the end, the research provides brief explanations regarding specific research findings per each model, and further, suggests some policy implications for the development of more accurate crowd counting methodology at protests in Korea.

A Novel Approach to Mugshot Based Arbitrary View Face Recognition

  • Zeng, Dan;Long, Shuqin;Li, Jing;Zhao, Qijun
    • Journal of the Optical Society of Korea
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    • v.20 no.2
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    • pp.239-244
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    • 2016
  • Mugshot face images, routinely collected by police, usually contain both frontal and profile views. Existing automated face recognition methods exploited mugshot databases by enlarging the gallery with synthetic multi-view face images generated from the mugshot face images. This paper, instead, proposes to match the query arbitrary view face image directly to the enrolled frontal and profile face images. During matching, the 3D face shape model reconstructed from the mugshot face images is used to establish corresponding semantic parts between query and gallery face images, based on which comparison is done. The final recognition result is obtained by fusing the matching results with frontal and profile face images. Compared with previous methods, the proposed method better utilizes mugshot databases without using synthetic face images that may have artifacts. Its effectiveness has been demonstrated on the Color FERET and CMU PIE databases.