• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4467-4486
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• 2018

Trying to deal with the problem of low robustness of Copy-Move Forgery Detection (CMFD) under various transformation and degradation attacks, a novel CMFD method is proposed in this paper. The main advantages of proposed work include: (1) Discrete Analytical Fourier-Mellin Transform (DAFMT) and Locality Sensitive Hashing (LSH) are combined to extract the block features and detect the potential copy-move pairs; (2) The Euclidian distance is incorporated in the pixel variance to filter out the false potential copy-move pairs in the post-verification step. In addition to extracting the effective features of an image block, the DAMFT has the properties of rotation and scale invariance. Unlike the traditional lexicographic sorting method, LSH is robust to the degradations of Gaussian noise and JEPG compression. Because most of the false copy-move pairs locate closely to each other in the spatial domain or are in the homogeneous regions, the Euclidian distance and pixel variance are employed in the post-verification step. After evaluating the proposed method by the precision-recall-$F_1$ model quantitatively based on the Image Manipulation Dataset (IMD) and Copy-Move Hard Dataset (CMHD), our method outperforms Emam et al.'s and Li et al.'s works in the recall and $F_1$ aspects.

• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.155-162
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• 2008

The quality of the fruits is measured by a lot of parameters. The grader of the fruits to measure the size of them is using the rotation drum method. Therefore when we classify the size of the fruits, they will be damaged. Also the optical grader used for estimating the degree of the saccharinity will incur high cost for it. In the proposed system, to select the characteristics of the fruits, three cameras are used. Because the information such as the volume and the degree of the maturity is used to classify the fruits, the degree of the saccharinity can't be estimated itself, but the information such as the color and the damage of the fruits can be estimated. Therefore, because we don't need the digital image with high resolution, we can develop the grader system of the fruit with low cost. To evaluate the performance of the proposed system, we compared it with the sight estimation and then we classified the sample. The result shows the accuracy of 96.7%.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.4
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• pp.116-123
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• 2009

Feature point matching, which is finding the corresponding points from two images with different viewpoint, has been used in various vision-based applications and the demand for the real-time operation of the matching is increasing these days. This paper presents a real-time feature point matching method by using a local descriptor derived by Zernike moments. From an input image, we find a set of feature points by using an existing fast corner detection algorithm and compute a local descriptor derived by Zernike moments at each feature point. The local descriptor based on Zernike moments represents the properties of the image patch around the feature points efficiently and is robust to rotation and illumination changes. In order to speed up the computation of Zernike moments, we compute the Zernike basis functions with fixed size in advance and store them in lookup tables. The initial matching results are acquired by an Approximate Nearest Neighbor (ANN) method and false matchings are eliminated by a RANSAC algorithm. In the experiments we confirmed that the proposed method matches the feature points in images with various transformations in real-time and outperforms existing methods.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.4
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• pp.607-616
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• 2014

Face recognition is a big challenge in surveillance system since different rotation angles of the face make the difficulty to recognize the face of the same person. This paper proposes a novel method to recognize face with different head poses by using 3D information of the face. Firstly, head pose estimation (estimation of different head pose angles) is accomplished by the POSIT algorithm. Then, 3D face image data is constructed by using head pose estimation. After that, 2D image and the constructed 3D face matching is performed. Face verification is accomplished by using commercial face recognition SDK. Performance evaluation of the proposed method indicates that the error range of head pose estimation is below 10 degree and the matching rate is about 95%.

• The KIPS Transactions:PartB
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• v.10B no.5
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• pp.561-566
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• 2003

This paper proposes a new algorithm that generates smooth and realistic transition views from one viewpoint to another view point on the panorama based navigation system. The proposed algorithm is composed with two steps. One is prewarping that aligns the viewing direction in two panorama image, the other is bidirectional disparity morphing (BDM) that generates the intermediate scene from the aligned panorama images. For the prewarping, first of all, we compute the phase correlation between two images in order to get the information such as the displacement, rotation, and scale. Then we align the original images using these information. As soon as finishing the prewarping, we compute the block based disparity vectors (DVs) and smooth them using the two occluding patterns. As we apply these DVs to the BDM, we can get the elaborate intermediate scenes. We make an experiment on the proposed algorithm with real panoramic images and we can get the satisfactory results.

• Journal of Aerospace System Engineering
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• v.12 no.2
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• pp.46-58
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• 2018

A two-axis gimbal-type X-band antenna is widely used to transmit bulk image data from high-resolution observation satellites. However, undesirable microvibrations induced by driving the antenna should be attenuated, because they are a main cause of image-quality degradation of the observation satellite. In this study, a pseudoelastic memory alloy (SMA) gear was proposed to attenuate the microvibrations by driving the antenna in an azimuth angle. In addition, the proposed gear can overcome the limitations of the conventional titanium blade gear, which is not still enough and is vulnerable to plastic deformations under excessive torque. To investigate the basic characteristics of the proposed SMA mesh washer gear, a static load test was performed on the thickness of the SMA mesh washer and the rotation of the gear. Moreover, The microvibration measurement test demonstrated that the SMA mesh washer gear proposed in this study is effective for microvibration attenuation.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.14 no.2
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• pp.83-96
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• 2011

The open space of apartment complex has changed diversely according to construction periods which were divided into the introduction stage (the 1980s), the development stage (the 1990s), and the maturity stage (after 1999). This study set out to analyze the periodic changes of visual characteristics and preference with the open space of apartment complexes in Cheongju City. For analysis of visual characteristics and preference, nineteen adjectives that were determined to sufficiently express the feeling of the open space of apartment complex. The results are as follows. As for adjective image assessment by using descriptive statistics, favorable images were shown in complexes of maturity stage phase that were constructed after the liberalization of apartment sale in 1999. These results may be caused both by quantitative increase and diversification of materials in planting and landscaping furniture and by nature-friendly designing. The results of factor analysis by Varimax rotation method showed that common variance was 73.9%, which indicates higher explanation. The nineteen adjectives could be divided into three factors, 'pleasantness factor,' 'negative factor,' and 'irregular factor.' Visual preference was analysed by using Least significant Difference (LSD) by analysis of variance : complexes of maturity stage phase that were constructed according to the liberalization of apartment sale in 1999 were highest in assessment. The correlation between view preference and adjective images was analyzed by multiple regression analysis, and 'feeling like walking,' 'well-arranged,' 'beautiful,' 'friendly,' and 'clean' (in order) were adjective images that most affected the preference. As for the analysis of the correlation between visual preference and physical components of view, the preference increased as the rate of pavement and greens was higher, while it decreased as size of building was larger. Therefore, backgrounds of walking and greens had strong effects on the preference.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.3
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• pp.267-274
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• 2009

Recently, UAVs (Unmanned Aerial Vehicles) are expected much as the Unmanned Systems for various missions. These missions are often based on the Vision System. Especially, missions such as surveillance and pursuit have a process which is carried on through the transmitted vision data from the UAV. In case of small UAVs, monocular vision is often used to consider weights and expenses. Research of missions performance using the monocular vision is continued but, actually, ground and target model have difference in distance from the UAV. So, 3D distance measurement is still incorrect. In this study, Mean-Shift Algorithm, Optical Flow and Subspace Method are posed to estimate the relative depth. Mean-Shift Algorithm is used for target tracking and determining Region of Interest (ROI). Optical Flow includes image motion information using pixel intensity. After that, Subspace Method computes the translation and rotation of image and estimates the relative depth. Finally, we present the results of this study using images obtained from the UAV experiments.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.815-822
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• 2003

Fingerprint image enhancement and minutiae matching are two key steps in an automatic fingerprint identification system. In this paper, we propose a fingerprint recognition technique by using minutiae linking information. Recognition process have three steps ; preprocessing, minutiae extraction, matching step based on minutiae pairing. After extracting minutiae of a fingerprint from its thinned image for accuracy, we introduce matching process using minutiae linking information. Introduction of linking information into the minutiae matching process is a simple but accurate way, which solves the problem of reference minutiae pair selection with low cost in comparison stage of two fingerprints. This algorithm is invariable to translation and rotation of fingerprint. The matching algorithm was tested on 500 images from the semiconductor chip style scanner, experimental result revealed the false acceptance rate is decreased and genuine acceptance rate is increased than existing method.

• KSCI Review
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• v.14 no.1
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• pp.265-271
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• 2006

In this paper, we propose a new automatic fingerprint identification system that identifies individuals in large databases. The algorithm consists of three steps: preprocessing, classification, and matching, in the classification, we present a new classification technique based on the statistical approach for directional image distribution. In matching, we also describe improved minutiae candidate pair extraction algorithm that is faster and more accurate than existing algorithm. In matching stage, we extract fingerprint minutiaes from its thinned image for accuracy, and introduce matching process using minutiae linking information. Introduction of linking information into the minutiae matching process is a simple but accurate way, which solves the problem of reference minutiae pair selection in comparison stage of two fingerprints quickly. This algorithm is invariant to translation and rotation of fingerprint. The proposed system was tested on 1000 fingerprint images from the semiconductor chip style scanner. Experimental results reveal false acceptance rate is decreased and genuine acceptance rate is increased than existing method.