• 한국HCI학회:학술대회논문집
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• 2008.02b
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• pp.298-303
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• 2008

Watching a program on IPTV among the numerous choices from the internet requires a burden of searching and browsing for a favorite one. This paper introduces a new concept called Mosaic Map and presents how it provides preview information of image map links to other programs. In Mosaic Map the pixels in the still image are used both as shading the background and as thumbnails which can link up with other programs. This kind of contextualized preview of choices can help IPTV users to associate the image with related programs without making visual saccades between watching IPTV and browsing many choices. The experiments showed that the Mosaic Map reduces the time to complete search and browsing, comparing to the legacy menu and web search.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.667-669
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• 2002

번호판 인식은 번호판 영역 추출 세그멘테이션, 인식의 3단계로 나눈다. 일반적으로 번호판 영역을 검출하는 과정에서 여러 후보영역이 추출되는데 검증 과정을 통해 그 중 하나를 선택한다. 따라서 적절한 검증 방법은 번호판 인식의 신뢰성을 높히기 위해 필수적이다. 본 논문은 다층 신경망에 사용하는 대표적인 알고리즘 중 하나인 역전과 알고리즘을 이용하여 번호판 후보 영역을 검증하는 방법을 제시한다. 신경망을 통한 학습을 위해 우선 적절한 훈련 이미지를 수집해야한다. 특히 번호판 이미지가 아닌 훈련 데이터를 수집하는 것은 어려운 문제이다. 본 논문에서는 효과석인 훈련 데이터 수집의 방법과 특징 벡터 생성에 대하여 제안하고 이 방법의 효용성을 실험을 통하여 검증한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.772-774
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• 2021

COVID-19 로 인해 마스크 착용이 필수적인 사회가 되면서 마스크를 착용한 상태로 얼굴 사진을 촬영하는 빈도가 증가하고 있다. 그러나 얼굴인식 기반의 보정 및 필터링 기능이 적용된 카메라 애플리케이션은 인물의 마스크 착용 유무를 인식하지 못하여 마스크로 가려진 영역까지 필터 및 색조 기능을 적용시킨다는 한계가 있다. 이러한 문제를 해결하기 위해 본 연구에서는 검출된 얼굴영역에서 마스크 착용 여부 및 마스크 영역을 판단하고 해당 영역을 제외한 나머지 얼굴 영역에 필터링 효과를 적용하는 기술을 구현하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.822-828
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• 2002

Optical flow estimation based on multi constraint approaches is frequently used for recognition of moving objects. However, the use have been confined because of OF estimation time as well as error problem. This paper shows a new method form effectively extracting movement information using the multi-constraint base approaches with sobel edge detection. The moving objects anr extraced in the input image sequence using edge detection and segmentation. Edge detection and difference of the two input image sequence gives us the moving objects in the images. The process of thresholding removes the moving objects detected due to noise. After thresholding the real moving objects, we applied the Combinatorial Hough Transform (CHT) and voting accumulation to find the optimal constraint lines for optical flow estimation. The moving objects found in the two consecutive images by using edge detection and segmentation greatly reduces the time for comutation of CHT. The voting based CHT avoids the errors associated with least squares methods. Calculation of a large number of points along the constraint line is also avoided by using the transformed slope-intercept parameter domain. The simulation results show that the proposed method is very effective for extracting optical flow vectors and hence recognizing moving objects in the images.

• The Journal of the Korea Contents Association
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• v.17 no.1
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• pp.137-144
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• 2017

Face detection is still a challenging task under severe face pose variations in complex background. This paper proposes an effective algorithm which can detect single or multiple faces based on skin color detection and depth information. We introduce Gaussian mixture model(GMM) for skin color detection in a color image. The depth information is from three dimensional depth sensor of Kinect V2 device, and is useful in segmenting a human body from the background. Then, a labeling process successfully removes non-face region using several features. Experimental results show that the proposed face detection algorithm can provide robust detection performance even under variable conditions and complex background.

• Communications for Statistical Applications and Methods
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• v.16 no.4
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• pp.615-625
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• 2009

In this paper we describe Wilcoxon test and T-test that are well-known in two-sample location problem for detecting edges under different window configurations. The choice of window configurations is an important factor in determining the performance and the expense of edge detectors. Our edge detectors are based on testing the mean values of local neighborhoods obtained under the edge model using an edge-height parameter. We compare three window configurations based on statistical tests in terms of qualitative measures with the edge maps and objective, quantitative measures as well as CPU time for detecting edge.

• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.7-14
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• 2019

In this paper, we propose a Cascade Classifier face detection method using the Haar-like feature, which is complemented by the Flood Fill algorithm for lossy areas due to illumination and shadow in YCbCr color space extraction. The Cascade Classifier using Haar-like features can generate noise and loss regions due to lighting, shadow, etc. because skin color extraction using existing YCbCr color space in image only uses threshold value. In order to solve this problem, noise is removed by erosion and expansion calculation, and the loss region is estimated by using the Flood Fill algorithm to estimate the loss region. A threshold value of the YCbCr color space was further allowed for the estimated area. For the remaining loss area, the color was filled in as the average value of the additional allowed areas among the areas estimated above. We extracted faces using Haar-like Cascade Classifier. The accuracy of the proposed method is improved by about 4% and the detection rate of the proposed method is improved by about 2% than that of the Haar-like Cascade Classifier by using only the YCbCr color space.

• Journal of the Korea Computer Graphics Society
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• v.23 no.3
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• pp.65-75
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• 2017

As a 360-degree image carries information of all directions, it often has too much information. Moreover, in order to investigate a 360-degree image on a 2D display, a user has to either click and drag the image with a mouse, or project it to a 2D panorama image, which inevitably introduces severe distortions. In consequence, investigating a 360-degree image and finding an object of interest in such a 360-degree image could be a tedious task. To resolve this issue, this paper proposes a method to find a region of interest and produces a 2D naturally looking image from a given 360-degree image that best matches a description given by a user in a natural language sentence. Our method also considers photo composition so that the resulting image is aesthetically pleasing. Our method first converts a 360-degree image to a 2D cubemap. As objects in a 360-degree image may appear distorted or split into multiple pieces in a typical cubemap, leading to failure of detection of such objects, we introduce a modified cubemap. Then our method applies a Long Short Term Memory (LSTM) network based object detection method to find a region of interest with a given natural language sentence. Finally, our method produces an image that contains the detected region, and also has aesthetically pleasing composition.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.11a
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• pp.90-92
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• 2018

본 논문에서는 입력 영상을 카메라의 자세 정보에 따라 적절히 와핑한 후 이들을 심(Seam)을 따라 이어붙인 360VR 에서 갑작스런 객체 출현에 의해 중첩 영역에서 발생하는 왜곡 문제를 해결할 방법을 제안한다. 임의의 객체가 나타났을 때, 객체의 윤곽선을 반영하여 심(Seam)을 재설정함으로써 객체가 우그러지거나, 잘려나가는 등의 왜곡 문제를 해결한다. 이를 위해 본 논문에서는 가우시안(Gaussian) 혼합 모델 기반 전경/배경분리에 의한 움직이는 객체 추출, 객체 윤곽선 검출, 윤곽선에 기반한 심(Seam) 조정, 새로운 심(Seam) 기반 스티칭으로 왜곡을 없애는 방법을 제안하였다. 그리고 이를 실제 촬영 영상에 적용하여 왜곡 개선 효과를 보였다.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.51-57
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• 2014

In this paper, we introduce the adaptive threshold detection scheme based on an evolutionary arithmetic algorithm for the M-ary holographic data storage(HDS) system. The genetic algorithm is a particular class of evolutionary arithmetic based on the process of biological evolution, which is a very promising technique for optimization problem and estimation applications. In this study, to improve the detection performance that is degraded by the HDS channel environment and the pixel misalignment, the threshold value was assumed to be a population set of the evolutionary algorithm. The proposed method can find an appropriate population set of bit threshold, which minimizes bit error rate(BER) as increased generation. For performance evaluation, we consider severe misalignment effect in the 4-ary holographic data storage system. Furthermore, we measure the BER performance and compare the proposed methods with the conventional threshold detection scheme, which verifies the superiority of the proposed scheme.