• Journal of KIISE:Databases
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• v.30 no.2
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• pp.134-144
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• 2003

Spatial relationships among objects are one of the important ingredients for expressing constraints of an image in image or multimedia retrieval systems. In this paper, we propose a unified image retrieval scheme using spatial relationships among objects and their features. The proposed scheme is especially effective in computing similarity between query image and images in the database. Also, objects and their spatial relationships are captured and annotated in XML. It could give better precision and flexibility in retrieving images from database. Finally, we have implemented a prototype system for retrieving images based on proposed technique and showed some of the experiment results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4567-4587
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• 2017

With the growth of the Internet and the extensive applications of image editing software, it has become easier to manipulate digital images without leaving obvious traces. Copy-move is one of the most common techniques for image forgery. Image blind forensics is an effective technique for detecting tampered images. This paper proposes an improved copy-move forgery detection method based on the discrete cosine transform (DCT). The quantized DCT coefficients, which are feature representations of image blocks, are truncated using a truncation factor to reduce the feature dimensions. A method for judging whether two image blocks are similar is proposed to improve the accuracy of similarity judgments. The main transfer vectors whose frequencies exceed a threshold are found to locate the copied and pasted regions in forged images. Several experiments are conducted to test the practicability of the proposed algorithm using images from copy-move databases and to evaluate its robustness against post-processing methods such as additive white Gaussian noise (AWGN), Gaussian blurring, and JPEG compression. The results of experiments show that the proposed scheme effectively detects both copied region and pasted region of forged images and that it is robust to the post-processing methods mentioned above.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.1
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• pp.8-18
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• 2008

In this paper, we propose an efficient algorithm using wavelet transform for still image database retrieval. Especially, it uses only the lowest frequency sub-band in multi-level wavelet transform so that a retrieval system uses a smaller quantity of memory and takes a faster processing time. We extract different textured features, statistical information such as mean, variance and histogram, from low frequency sub-band. Then we measure the distances between the query image and the images in a database in terms of these features. To obtain good retrieval performance, we use the first feature (mean and variance of wavelet coefficients) to filter out most of the unlikely images. The rest of the images are considered to be candidate images. Then we apply the second feature (histogram of wavelet coefficient) to rank all the candidate images. To evaluate the algorithm, we create various distorted image databases using MIT VisTex texture images and PICS natural images. Through simulations, we demonstrate that our method can achieve performance satisfactorily in terms of the retrieval accuracy as well as the both memory requirement and computational complexity. Therefore it is expected to provide good retrieval solution for JPEG-2000 using wavelet transform.

• Imaging Science in Dentistry
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• v.50 no.1
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• pp.45-52
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• 2020

Purpose: This study was conducted to develop an evidence-based clinical imaging diagnostic guideline for implant planning, taking into account efficacy, benefits, and risks. Materials and Methods: The guideline development process employed the adaptation methodology used for Korean clinical imaging guidelines(K-CIG). Core databases(Ovid-Medline, Ovid-Embase, National Guideline Clearinghouse, Guideline International Network) and domestic databases (KoreaMed, KMbase, and KoMGI) were searched for guidelines. The retrieved articles were analyzed by 2 reviewers, and articles were selected using well-established inclusion criteria. Results: The search identified 294 articles, of which 3 were selected as relevant guidelines. Based on those 3 guidelines, 3 recommendations for implant planning were derived. Conclusion: We recommend radiography or cone-beam computed tomography (CBCT) scanning for individual patients judged to require a cross-sectional image after reading of a panoramic X-ray image and a conventional intraoral radiological image. Various steps should be taken to raise awareness of these recommendations among clinicians and the public, and K-CIG should be regularly reviewed and revised.

• Journal of the Korea Society of Computer and Information
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• v.24 no.10
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• pp.91-99
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• 2019

In this paper, we propose partial denoising boundary matching based on an index for faster matching in very large image databases. Attempts have recently been made to convert boundary images to time-series with the objective of solving the partial denoising problem in boundary matching. In this paper, we deal with the disk I/O overhead problem of boundary matching to support partial denoising in a large image database. Although the solution to the problem superficially appears trivial as it only applies indexing techniques to boundary matching, it is not trivial since multiple indexes are required for every possible denoising parameters. Our solution is an efficient index-based approach to partial denoising using $R^*-tree$ in boundary matching. The results of experiments conducted show that our index-based matching methods improve search performance by orders of magnitude.

• Journal of Information Processing Systems
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• v.12 no.1
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• pp.83-99
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• 2016

The latest research on the image-based fingerprint matching approaches indicates that they are less complex than the minutiae-based approaches when it comes to dealing with low quality images. Most of the approaches in the literature are not robust to fingerprint rotation and translation. In this paper, we develop a robust fingerprint matching system by extracting the circular region of interest (ROI) of a radius of 50 pixels centered at the core point. Maximizing their orientation correlation aligns two fingerprints that are to be matched. The modified Euclidean distance computed between the extracted orientation features of the sample and query images is used for matching. Extensive experiments were conducted over four benchmark fingerprint datasets of FVC2002 and two other proprietary databases of RFVC 2002 and the AITDB. The experimental results show the superiority of our proposed method over the well-known image-based approaches in the literature.

• Genomics & Informatics
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• v.7 no.3
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• pp.168-170
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• 2009

The explosion in biological data resulting from high-throughput experiments requires new software tools to manipulate and display pathways in a way that can integrate disparate sources of information. A visual Java-based CAD tool for drawing and annotating biological pathways with semiautomatic image-processing features is described in this paper. The result of the image-editing process is an XML file for the appropriate links. This tool integrates the pathway images and XML file sources. The system has facilities for linking graphical objects to external databases and is capable of reproducing existing visual representations of pathway maps.

• Journal of Electrical Engineering and Technology
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• v.10 no.2
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• pp.659-669
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• 2015

Face Recognition assumes much significance in the context of security based application. Normally, high resolution images offer more details about the image and recognizing a face from a reasonably high resolution image would be easier when compared to recognizing images from very low resolution images. This paper addresses the problem of recognizing faces from a very low resolution image whose size is as low as $8{\times}8$. With the use of CCTV(Closed Circuit Television) and with other surveillance camera-based application for security purposes, the need to overcome the shortcomings with very low resolution images has been on the rise. The present day face recognition algorithms could not provide adequate performance when employed to recognize images from VLR images. Existing methods use super-resolution (SR) methods and Relation Based Super Resolution methods to construct from very low resolution images. This paper uses a learning based super resolution method to extract and construct images from very low resolution images. Experimental results show that the proposed SR algorithm based on relationship learning outperforms the existing algorithms in public face databases.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1847-1850
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• 2003

In many image-coding applications such as web browsing, image databases, and telemedicine, it is needed that only a region of interest(ROI) is transmitted and then reconstructed first before the whole image is transmitted and reconstructed. The Maxshift method has been used as a standard one in this research about ROI coding in JPEG2000. However Maxshift method can process only one ROI, this paper suggests an improved Maxshift method which can process Multiple ROI haying the priority order. In this method, the ROI coefficient which has the high priority order can be moved to upward two bit plane in order to process multiple ROI.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.482-484
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• 1998

Abstract : Multimedia data now one of the widely used information in all the fields as the fast developments of computer techniques have been made. Traditional database systems based on textual information have limitations when applied to multimedia information. This is because simple textual descriptions are ambiguous and inadequate for searching multimedia information for multimedia databases and digital libraries. Thus, especially for image data, which is one of the important multimedia information types, which can retrieve and browse image data on the basis of pictorial queries. Therefore, this paper presents an efficient method for describing texture information in image data.