• Convergence Security Journal
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• v.2 no.2
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• pp.99-108
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• 2002

In this paper, I propose a reference image updating algorithm for Intruder Detection System using a difference image method that can reliably separate moving objects from noisy background in the image sequence received from a camera at the fixed position. The proposed algorithm consists of four process determines threshold value and quantization, segmentation of a moving object area, generation of adaptive temporary image that removes a moving object area, and updates reference image using median filtering. The test results show that the proposed algorithm can generate reference image very effectively in the noisy environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.5C
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• pp.536-541
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• 2007

In video coding standard H.264/AVC, motion estimation using multiple reference pictures improves compression efficiency but the efficiency depends upon image content not the number of reference pictures. So, the motion estimation includes a large amount of computation of no worth according to image. This paper proposes fast motion estimation algorithm that removes worthless computation in the motion estimation using multiple reference pictures. The proposed algorithm classifies a block into valid and invalid blocks for the multiple reference pictures and removes the workless computation by applying a single reference picture to the invalid block. To estimate the proposed algorithm's performance, image quality, bit rate, and motion estimation time are compared with ones of the conventional algorithm in the reference software JM 9.5. The simulation results show that the proposed algorithm can considerably save about 38.67% the averaged motion estimation time while keeping the image quality and the bit rate, whose are average values are -0.02dB and -0.77% respectively, as good as the conventional algorithm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.455-456
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• 2008

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.4
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• pp.671-685
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• 2023

By applying artificial intelligence to image editing technology, it has become possible to generate high-quality images with minimal traces of manipulation. However, since these technologies can be misused for criminal activities such as dissemination of false information, destruction of evidence, and denial of facts, it is crucial to implement strong countermeasures. In this study, image file and mobile forensic artifacts analysis were conducted for detecting image manipulation. Image file analysis involves parsing the metadata of manipulated images and comparing them with a Reference DB to detect manipulation. The Reference DB is a database that collects manipulation-related traces left in image metadata, which serves as a criterion for detecting image manipulation. In the mobile forensic artifacts analysis, packages related to image editing tools were extracted and analyzed to aid the detection of image manipulation. The proposed methodology overcomes the limitations of existing graphic feature-based analysis and combines with image processing techniques, providing the advantage of reducing false positives. The research results demonstrate the significant role of such methodology in digital forensic investigation and analysis. Additionally, We provide the code for parsing image metadata and the Reference DB along with the dataset of manipulated images, aiming to contribute to related research.

• Journal of Broadcast Engineering
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• v.18 no.3
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• pp.463-473
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• 2013

In this paper, we propose a super-resolution (SR) image reconstruction algorithm using multi-view images. We acquire 25 images from multi-view cameras, which consist of a $5{\times}5$ array of cameras, and then reconstruct an SR image of the center image using a low resolution (LR) input image and the other 24 LR reference images. First, we estimate disparity maps from the input image to the 24 reference images, respectively. Then, we interpolate a SR image by employing the LR image and matching points in the reference images. Finally, we refine the SR image using an iterative regularization scheme. Experimental results demonstrate that the proposed algorithm provides higher quality SR images than conventional algorithms.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.1
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• pp.101-109
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• 2011

This paper describes the attempts to improve the performance of an image matching method for multiple image. Typically, matching between two images is performed by using correlation between a reference and corresponding images. The proposed multiple image matching algorithm performs matching in an object space, chooses the image closest to the true vertical image as a reference image, calculates the correlation based on the chosen reference image. The algorithm also detects occluded regions automatically and keep them from matching. We could find that it is possible to create high quality DEM by this method, regardless of the location of image. From the performance improvement experiments through the occlusion detection, we could confirm the possibility of a more accurate representation of 3D information.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.6
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• pp.267-274
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• 2023

In this paper, a method for estimating the illuminant chromaticity of a scene for an input image is proposed. The illuminant chromaticity is estimated using the illuminant reference region. The conventional method uses a certain number of reference lighting information. By comparing the chromaticity distribution of pixels from the input image with the chromaticity set prepared in advance for the reference illuminant, the reference illuminant with the largest overlapping area is regarded as the scene illuminant for the corresponding input image. In the process of calculating the overlapping area, the weights for each reference light were applied in the form of a Gaussian distribution, but a clear standard for the variance value could not be presented. The proposed method extracts an independent reference chromaticity region from a given reference illuminant, calculates the characteristic values in the r-g chromaticity plane of the RGB color coordinate system for all pixels of the input image, and then calculates the independent chromaticity region and features from the input image. The similarity is evaluated and the illuminant with the highest similarity was estimated as the illuminant chromaticity component of the image. The performance of the proposed method was evaluated using the database image and showed an average of about 60% improvement compared to the conventional basic method and showed an improvement performance of around 53% compared to the conventional Gaussian weight of 0.1.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.1
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• pp.1-6
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• 2018

In this paper, we propose the method to eliminate repetitive processes for key-point detection on multi-scale image space. The proposed method detects key-points from the original image, and select a good key-points using the cluster filters, and create the key-point clusters. And it select reference objects by using direction angles of the key-point clusters, predict the scale of the original image by using the distributed distance ratio. It transform the scale of the reference image, and apply the detection of key-points to the transformed reference image. In the results of the experiment, the proposed method can be found to improve the key-points detection time by 75 % and 71 % compared to SIFT method and scaled ORB method using the multi-scale images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12B
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• pp.2415-2423
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• 1999

We propose a new optical method which conceals the data of authorized persons by encryption before they are stored or compared in the pattern recognition system for security systems. This proposed security system is made up of two subsystems : a proposed optical encryption system and a pattern recognition system based on the JTC which has been shown to perform well. In this system, each image of authorized persons as a reference image is stored in memory units through the proposed encryption system. And if a fingerprint image is placed in the input plane of this security system for access to a restricted area, the image is encoded by the encryption system then compared with the encrypted reference image. Therefore because the captured input image and the reference data are encrypted, it is difficult to decrypt the image if one does not know the encryption key bit stream. The basic idea is that the input image is encrypted by performing optical XOR operations with the key bit stream that is generated by digital encryption algorithms. The optical XOR operations between the key bit stream and the input image are performed by the polarization encoding method using the polarization characteristics of LCDs. The results of XOR operations which are detected by a CCD camera should be used as an input to the JTC for comparison with a data base. We have verified the idea proposed here with computer simulations and the simulation results were also shown.

• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.67-72
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• 2007

In this paper, we present a construction method using perspective model which allows for the representation of the motion of a planar surface under perspective projection. The motion parameters are obtained by minimizing a disparity measure between the region in the current frame and the mapped region in the previous frame. The frames are constructed with dynamic panoramic image using a fixed reference or a time varying reference. By experiment, panoramic image proposed in this paper represents contents more efficiently than static image or video, and has a high volume reduction ratio.