• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.3
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• pp.217-226
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• 2003

A novel fingerprint ridge feature extraction using sequential labeling of thinned fingerprint image is proposed, which is invariant to position translation, scaling, and rotation. the proposed algorithm labels ridges of thinned fingerprint image sequentially using vertical line that goes through fingerprint core point. Then, we extract a feature from each labeled ridge and the extraction process is based on the type fo the ridge and a minutiae ridge angle in the ridge. The feature extracted through this process enables us to find out the kind of various minutiae and minutiae angle. As a result of the experiment using two thinned fingerprint images, we finally confirm that proposed algorithm is not related to position translation, scaling, and rotation.

• The KIPS Transactions:PartB
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• v.10B no.4
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• pp.459-464
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• 2003

This paper proposes the use of a wavelet based image transform algorithm in human iris recognition method and the effectiveness of this technique will be determined in preprocessing of extracting Iris image from the user´s eye obtained by imaging device such as CCD Camera or due to torsional rotation of the eye, and it also resolves the problem caused by invariant under translations and dilations due to tilt of the head. This technique values through the proposed translation-invariant wavelet transform algorithm rather than the conventional wavelet transform method. Therefore we extracted the best-matching iris feature values and compared the stored feature codes with the incoming data to identify the user. As result of our experimentation, this technique demonstrate the significant advantage over verification when it compares with other general types of wavelet algorithm in the measure of FAR & FRR.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.11a
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• pp.41-43
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• 2019

Image-to-image 변환에서 인상적인 성능을 보이는 StarGAN 은 모델의 성능에 중요한 영향을 끼치는 adversarial weight, classification weight, reconstruction weight 라는 세가지 하이퍼파라미터의 결정을 전제로 하고 있다. 본 연구에서는 이 중 conditional GAN loss 인 adversarial loss 와 classification loss 를 대치할 수 있는 attribute loss를 제안함으로써, adversarial weight와 classification weight 를 최적화하는 데 걸리는 시간을 attribute weight 의 최적화에 걸리는 시간으로 대체하여 하이퍼파라미터 탐색에 걸리는 시간을 획기적으로 줄일 수 있게 하였다. 제안하는 attribute loss 는 각 특징당 GAN 을 만들 때 각 GAN 의 loss 의 합으로, 이 GAN 들은 hidden layer 를 공유하기 때문에 연산량의 증가를 거의 가져오지 않는다. 또한 reconstruction loss 를 단순화시켜 연산량을 줄인 simplified content loss 를 제안한다. StarGAN 의 reconstruction loss 는 generator 를 2 번 통과하지만 simplified content loss 는 1 번만 통과하기 때문에 연산량이 줄어든다. 또한 이미지 Framing 을 통해 배경의 왜곡을 방지하고, 양방향 성장을 통해 학습 속도를 향상시킨 아키텍쳐를 제안한다.

• Journal of Korea Society of Industrial Information Systems
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• v.6 no.1
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• pp.33-38
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• 2001

In this paper, we present an image retrieval system using shape features. The preprocessing to gain shape feature includes edge extraction using chain code. The shape features consist of center of mass, standard deviation, ratio of major axis and minor axis length. The similarity is estimated as comparing the features of query image with the features of images in database. Thus, the candidates of images are retrieved according to the order of similarity. The result of an experimentation is dullness for scale, rotation and translation. We evaluate the performance of shape features for image retrieval on a database with over 170 images. The Recall and the Precision is each 0.72 and 0.83 in the result of average experiment. So the proposed method is presented useful method.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.2
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• pp.349-354
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• 2023

As the population interested in interior design has been increasing, the global interior market has grown significantly. Global interior companies are developing and providing simulation services for various interior elements. Although wallpaper design is the most important interior element, existing wallpaper design simulation services are difficult to use due to drawbacks such as differences between expected and actual results, long simulation time, and the need for professional skills. We proposed a wallpaper image transformation method for interior design using cycle generative adversarial networks (GAN). The proposed method demonstrates that users can simulate wallpaper design within a short period of time based on interior image data using various types of wallpaper.

• Progress in Medical Physics
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• v.19 no.2
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• pp.120-124
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• 2008

In this study, we developed the protopype of QA phantom for image QA including an additional component for image based radiation treatment system. The new phantom considered two main parts: Image quality and fusion accuracy. Image quality part included for daily CT number linearity and spatial resolution, and fusion accuracy part designed to simulate a simple translation-rotation setting. The CT scans of the phantom obtained from conventional CT, MVCT of Tomotherapy unit, and both image sets were satisfied the recommendation of spatial resolution. This phantom was simple and efficient for daily imaging QA, and it is important to provide a new concept of verification of image registration.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.2
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• pp.1-8
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• 2003

This paper proposes an object-based image retrieval technique based on the dominant color pair information. Most of existing methods for content based retrieval extract the features from an image as a whole, instead of an object of interest. As a result, the retrieval performance tends to degrade due to the background colors. This paper proposes an object based retrieval scheme, in which an object of interest is used as a query and the similarity is measured on candidate regions of DB images where the object may exist. From the segmented image, the dominant color pair information between adjacent regions is used for selecting candidate regions. The similarity between the query image and DB image is measured by using the color correlogram technique. The dominant color pair information is robust against translation, rotation, and scaling. Experimental results show that the performance of the proposed method has been improved by reducing the errors caused by background colors.

• Journal of Broadcast Engineering
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• v.17 no.1
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• pp.17-25
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• 2012

In this paper, we propose a method of producing a stereoscopic image from multiple images captured from a monoscopic camera. By translating a camera in the horizontal direction, left and right images are chosen among N captured images. For this, image edges are extracted and a rotational angle is estimated from edge orientation. Also, a translational vector is also estimated from the correlation of projected image data. Then, two optimal images are chosen and subsequently compensated using the rotational angle as well as the translational vector in order to make a satisfactory stereoscopic image. The proposed method was performed on thirty-two test image set. The subjective visual fatigue test was carried out to validate the 3D quality of stereoscopic images. In terms of visual fatigue, the 3D satisfaction ratio reached approximately 84%.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.6
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• pp.667-675
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• 2011

In this paper, we propose an automatic image-to-image registration between high resolution multi-sensor images. To do this, TerraSAR-X image was shifted according to the initial translation differences of the x and y directions between images estimated using Mutual Information method. After that, the Canny edge operator was applied to both images to extract linear features. These features were used to design a cost function that finds matching points based on the similarities of their locations and gradient orientations. For extracting large number of evenly distributed matching points, only one point within each regular grid constructed throughout the image was extracted to the final matching point pair. The model, which combined the piecewise linear function with the global affine transformation, was applied to increase the accuracy of the geometric correction, and the proposed method showed RMSE lower than 5m in all study sites.

• Journal of Korea Multimedia Society
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• v.25 no.10
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• pp.1535-1545
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• 2022

Sign language has completely different meaning depending on the direction of the hand or the change of facial expression even with the same gesture. In this respect, it is crucial to capture the spatial-temporal structure information of each movement. However, sign language translation studies based on Sign2Gloss2Text only convey comprehensive spatial-temporal information about the entire sign language movement. Consequently, detailed information (facial expression, gestures, and etc.) of each movement that is important for sign language translation is not emphasized. Accordingly, in this paper, we propose Spatial-temporal Keypoints Centered Sign2Gloss2Text Translation, named STKC-Sign2 Gloss2Text, to supplement the sequential and semantic information of keypoints which are the core of recognizing and translating sign language. STKC-Sign2Gloss2Text consists of two steps, Spatial Keypoints Embedding, which extracts 121 major keypoints from each image, and Temporal Keypoints Embedding, which emphasizes sequential information using Bi-GRU for extracted keypoints of sign language. The proposed model outperformed all Bilingual Evaluation Understudy(BLEU) scores in Development(DEV) and Testing(TEST) than Sign2Gloss2Text as the baseline, and in particular, it proved the effectiveness of the proposed methodology by achieving 23.19, an improvement of 1.87 based on TEST BLEU-4.