• Journal of Digital Contents Society
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• v.14 no.4
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• pp.447-454
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• 2013

As the surveillance CCTVs are increasing every year, big data image processing for the CCTV image data has become a hot issue. In this paper, we propose a Hadoop-based big data image processing technique to recognize a vehicle number from a large amount of automatic number plate images taken from CCTVs. We also implement the vehicle route tracking system that displays the moving path of the searched vehicle on Google Maps with the related information together. In order to evaluate the performance we compare and analysis the vehicle number recognition time for a lot of CCTV image data in Hadoop and the single PC environment.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.1
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• pp.67-73
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• 2008

The most common method of pipeline inspection is to use a remote-controlled-machine equipped with a CCTV, which, however, has many limitations to accurately inspect pipeline condition. In case of a typical CCTV, since the camera looks at the end point of the pipe, the locations of the defects and distance-readings are often different. In addition, the quality and accuracy of the inspection is highly dependent on the operator's skill and experience. In this research a new system is developed by use of the image processing techniques and the lens combination. The image acquisition system is developed that acquires the front and the side view of the pipe simultaneously. Side view unwrapping and stitching technology using image process techniques are developed which delivers high resolution image data.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.5
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• pp.58-65
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• 2016

Recent frequent occurrence of urban sinkhole serves as a momentum of the periodic inspection of sewer pipelines. Sewer inspection using a CCTV device needs a lot of time and efforts. Many of previous studies which reduce the laborious tasks are mainly interested in the developments of image processing S/W and inspection H/W. However there has been no attempt to find meaningful information from the existing CCTV images stored by the sewer maintenance manager. This study adopts a cross-correlation based image processing method and extracts location data of sewer inspection device from CCTV images. As a result of the analysis of time-location relation, it shows strong correlation between the device's stand times and the sewer damages. In case of using this method to investigate sewer inspection CCTV images, it will save the investigator's efforts and improve the sewer maintenance efficiency and reliability.

• Convergence Security Journal
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• v.12 no.2
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• pp.43-51
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• 2012

CCTV would be the effective way in the prevention of abuse, as well as recorded image information evidence of the crime as a significant legal effect. But recorded image information As evidence by utilizing the Complaint/complaint handling, and administrative business processes that are currently operating offline procedural complexity and unnecessary time appear costly, privacy remains an issue to be solved, etc. Runoff. In this paper, incidence rate of offline business processing phase to solve the problems proposed to build unified portal for CCTV image information and the existing studies on the effectiveness of electronic civil service system, previous studies by analyzing e-government in accordance with laws and privacy laws, CCTV image information portal deployment model is applied to data integration occurs are trying to solve the problem effectively.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.5
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• pp.219-227
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• 2012

This paper describes the design and implementation of an efficient image security system for CCTV using the analysis technique of color informations. In conventional approaches, the compression and encryption techniques are mainly used for reducing the data size of the original images while the analysis technique of color information is first proposed, which eliminates the overlapping part of the original image data in our approach. In addition, security-enhanced CCTV image security system is presented using SSL/VPN tunneling technique. When we use the method proposed in this paper, an efficient image processing is enable for a mount of information, and also security problem is enhanced. Through the implementation results, the proposed method showed that the original image information are dramatically reduced.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.26 no.3
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• pp.272-277
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• 2017

CCTV image processing techniques have been developed for safety management in manufacturing sites. However, CCTV growth has become a social problem for video surveillance with regard to privacy. This study aims to manage the safety system efficiently and protect privacy simultaneously. In this study, the CCTV monitoring system is composed of five steps (accident monitoring, detection, notification, management, restoration). De-identified image is observed when we are in a normal situation. De-identified image changes to identified image when it detects an accident. As soon as it detects an accident, the accident information is sent to the safety administrator. Then the administrator could conduct safety measures. Afterward, accumulated accident data could be used for statistical data that could be utilized as analyzing expecting accident.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.967-974
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• 2012

In this paper, a vehicle detection algorithm with HD CCTV camera images using GMM(Gaussian Mixture Model) algorithm and mathematical morphological processing is proposed. At the first stage, background could be estimated using GMM from CCTV input image signal and then object could be separated from difference image of the input image and background image. At the second stage, candidated object were reformed by using mathematical morphological processing. Finally, vehicle object could be detected using vehicle size informations depend on distance and vehicle type in tunnel. Through real experiments in tunnel, it is shown that the proposed system works well.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.4
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• pp.462-469
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• 2019

According to the survey of Ministry of the Interior and Safety in Korea, The number of public and private CCTV reached over ten million and is still increasing. Also with improving Image Processing Technology, it is possible to obtain diverse information. Recently, various services using CCTV are being provided. Therefore it is necessary to ensure CCTV image integrity. However there is no system to prove events in film yet. In this paper, we suggest system model that can manage, use and authenticate CCTV. This model allows a CCTV film to be verified by other nearby CCTVs' data. This model ensures film's integrity by using blockchain. And also, It addresses privacy problem in CCTV and file size problem in blockchain by using not large film data but much smaller analyzed data.

• Journal of Information Processing Systems
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• v.19 no.6
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• pp.767-777
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• 2023

In modern society, user privacy is emerging as an important issue as closed-circuit television (CCTV) systems increase rapidly in various public and private spaces. If CCTV cameras monitor sensitive areas or personal spaces, they can infringe on personal privacy. Someone's behavior patterns, sensitive information, residence, etc. can be exposed, and if the image data collected from CCTV is not properly protected, there can be a risk of data leakage by hackers or illegal accessors. This paper presents an innovative approach to "machine learning based reversible chaotic masking method for user privacy protection in CCTV environment." The proposed method was developed to protect an individual's identity within CCTV images while maintaining the usefulness of the data for surveillance and analysis purposes. This method utilizes a two-step process for user privacy. First, machine learning models are trained to accurately detect and locate human subjects within the CCTV frame. This model is designed to identify individuals accurately and robustly by leveraging state-of-the-art object detection techniques. When an individual is detected, reversible chaos masking technology is applied. This masking technique uses chaos maps to create complex patterns to hide individual facial features and identifiable characteristics. Above all, the generated mask can be reversibly applied and removed, allowing authorized users to access the original unmasking image.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.2
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• pp.83-90
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• 2015

Almost of current Automatic Incident Detection(AID) algorithms involve the vulnerability that detects the traffic accident in open road or in tunnel as the traffic jam not as the traffic accident. This paper proposes the improved accident detection algorithm to enhance the detection probability based on accident detection algorithms applied in open roads. The improved accident detection algorithm provides the preliminary judgment of potential accident by detecting the stopped object by Gaussian Mixture Model. Afterwards, it measures the detection area is divided into blocks so that the occupancy rate can be determined for each block. All experimental results of applying the new algorithm on a real incident was detected image without error.