• Title/Summary/Keyword: 벡터사진

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Passports Recognition using ART2 Algorithm and Face Verification (ART2 알고리즘과 얼굴 인증을 이용한 여권 인식)

  • Jang, Do-Won;Kim, Kwang-Baek
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2005.05a
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    • pp.190-197
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    • 2005
  • 본 논문에서는 출입국자 관리의 효율성과 체계적인 출입국 관리를 위하여 여권 코드를 자동으로 인식하고 위조 여권을 판별할 수 있는 여권 인식 및 얼굴 인증 방법을 제안한다. 여권 이미지는 기울어진 상태로 스캔되어 획득되어질 수도 있으므로 기울기 보정은 문자 분할 및 인식, 얼굴 인증에 있어 매우 중요하다. 따라서 본 논문에서는 여권 영상을 스미어링한 후, 추출된 문자열 중에서 가장 긴 문자열을 선택하고 이 문자열의 좌측과 우측 부분의 두께 중심을 연결하는 직선과 수평선과의 기울기를 이용하여 여권 여상에 대한 각도 보정을 수행한다. 여권 코드 추출은 소벨 연산자와 수평 스미어링, 8방향 윤곽선 추적 알고리즘을 적용하여 여권 코드의 문자열 영역을 추출하고, 추출된 여권 코드 문자열 영역에 대해 반복 이지화 방법을 적용하여 코드의 문자열 영역을 이진화한다. 이진화된 문자열 영역에 대해 CDM 마스크를 적용하여 문자열의 코드들을 복원하고 8방향 윤곽선 추적 알고리즘을 적용하여 개별 코드를 추출한다. 추출된 개별 코드는 ART2 알고리즘을 적용하여 인식한다. 얼굴 인증을 위해 템플릿 매칭 알고리즘을 이용하여 얼굴 템플릿 데이터베이스를 구축하고 여권에서 추출된 얼굴 영역과의 유사도 측정을 통하여 여권 얼굴 영역의 위조 여부를 판별한다. 얼굴 인증을 위해서 Hue, YIQ-I, YCbCr-Cb 특징들의 유사도를 종합적으로 분석하여 얼굴 인증에 적용한다. 제안된 여권 인식 및 얼굴 인증 방법의 성능을 평가를 위하여 원본 여권에 얼굴 부분을 위조한 여권과 노이즈, 대비 증가 및 감소, 밝기 증가 및 감소 및 여권 영상을 흐리게 하여 실험한 결과, 제안된 방법이 여권 코드 인식 및 얼굴 인증에 있어서 우수한 성능이 있음을 확인하였다.권 영상에서 획득되어진 얼굴 영상의 특징벡터와 데이터베이스에 있는 얼굴 영상의 특징벡터와의 거리 값을 계산하여 사진 위조 여부를 판별한다. 제안된 여권 인식 및 얼굴 인증 방법의 성능을 평가를 위하여 원본 여권에서 얼굴 부분을 위조한 여권과 기울어진 여권 영상을 대상으로 실험한 결과, 제안된 방법이 여권의 코드 인식 및 얼굴 인증에 있어서 우수한 성능이 있음을 확인하였다.진행하고 있다.태도와 유아의 창의성간에는 상관이 없는 것으로 나타났고, 일반 유아의 아버지 양육태도와 유아의 창의성간의 상관에서는 아버지 양육태도의 성취-비성취 요인에서와 창의성제목의 추상성요인에서 상관이 있는 것으로 나타났다. 따라서 창의성이 높은 아동의 아버지의 양육태도는 일반 유아의 아버지와 보다 더 애정적이며 자율성이 높지만 창의성이 높은 아동의 집단내에서 창의성에 특별한 영향을 더 미치는 아버지의 양육방식은 발견되지 않았다. 반면 일반 유아의 경우 아버지의 성취지향성이 낮을 때 자녀의 창의성을 향상시킬 수 있는 것으로 나타났다. 이상에서 자녀의 창의성을 향상시키는 중요한 양육차원은 애정성이나 비성취지향성으로 나타나고 있어 정서적인 측면의 지원인 것으로 밝혀졌다.징에서 나타나는 AD-SR맥락의 반성적 탐구가 자주 나타났다. 반성적 탐구 척도 두 그룹을 비교 했을 때 CON 상호작용의 특징이 낮게 나타나는 N그룹이 양적으로 그리고 내용적으로 더 의미 있는 반성적 탐구를 했다용을 지원하는 홈페이지를 만들어 자료 제공 사이트에 대한 메타 자료를 데이터베이스화했으며 이를 통해 학생들이 원하는 실시간 자료를 검색하여 찾을 수 있고 홈페이지를 방분했을 때 이해하기 어려운 그래프나 각 홈페이지가 제공하는 자료들에 대한 처리 방법을 도움말로 제공받을 수 있게 했다. 실

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Exploring the Applicability of Grain Size Trend Analysis to Understanding the Morphological Responses of the Deltaic Barrier Islands in the Nakdong River (낙동강 삼각주연안 사주섬의 지형변화에 대한 입도경향 분석의 활용도 탐색)

  • Kim, Sung-Hwan;Rhew, Ho-Sahng
    • Journal of the Korean association of regional geographers
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    • v.13 no.2
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    • pp.119-128
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    • 2007
  • Grain-size trend analysis is the methodology to obtain the net sediment transport pattern from the spatial trends of grain size parameters. It has the potentials to be an effective tool to address the morphological changes of the deltaic barrier islands in the Nakdoog River once we make sure net transport patterns inferred from grain size trend analysis represent the morphological evolution patterns. This research aims to investigate the applicability of the net transport patterns obtained by 'transport vector', proposed by Gao and Collins(1992), to understanding the morphological changes of the Nakdong River deltaic barrier islands. The results indicate that the net transport directions are overall in concordance with the morphological evolution patterns; however, the level of concordance is low in the island with fast growing rate. The reasons may be match or mismatch of temporal scales involved between processes represented by net transport patterns and morphological change analyzed or the rate of morphological change. Consequently, the application of grain size trend analysis in analyzing the morphological changes of deltaic barrier islands requires the careful consideration of temporal scales involved.

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Deep Learning Approach for Automatic Discontinuity Mapping on 3D Model of Tunnel Face (터널 막장 3차원 지형모델 상에서의 불연속면 자동 매핑을 위한 딥러닝 기법 적용 방안)

  • Chuyen Pham;Hyu-Soung Shin
    • Tunnel and Underground Space
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    • v.33 no.6
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    • pp.508-518
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    • 2023
  • This paper presents a new approach for the automatic mapping of discontinuities in a tunnel face based on its 3D digital model reconstructed by LiDAR scan or photogrammetry techniques. The main idea revolves around the identification of discontinuity areas in the 3D digital model of a tunnel face by segmenting its 2D projected images using a deep-learning semantic segmentation model called U-Net. The proposed deep learning model integrates various features including the projected RGB image, depth map image, and local surface properties-based images i.e., normal vector and curvature images to effectively segment areas of discontinuity in the images. Subsequently, the segmentation results are projected back onto the 3D model using depth maps and projection matrices to obtain an accurate representation of the location and extent of discontinuities within the 3D space. The performance of the segmentation model is evaluated by comparing the segmented results with their corresponding ground truths, which demonstrates the high accuracy of segmentation results with the intersection-over-union metric of approximately 0.8. Despite still being limited in training data, this method exhibits promising potential to address the limitations of conventional approaches, which only rely on normal vectors and unsupervised machine learning algorithms for grouping points in the 3D model into distinct sets of discontinuities.

Plant leaf Classification Using Orientation Feature Descriptions (방향성 특징 기술자를 이용한 식물 잎 인식)

  • Gang, Su Myung;Yoon, Sang Min;Lee, Joon Jae
    • Journal of Korea Multimedia Society
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    • v.17 no.3
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    • pp.300-311
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    • 2014
  • According to fast change of the environment, the structured study of the ecosystem by analyzing the plant leaves are needed. Expecially, the methodology that searches and classifies the leaves from captured from the smart device have received numerous concerns in the field of computer science and ecology. In this paper, we propose a plant leaf classification technique using shape descriptor by combining Scale Invarinat Feature Transform (SIFT) and Histogram of Oriented Gradient (HOG) from the image segmented from the background via Graphcut algorithm. The shape descriptor is coded in the field of Locality-constrained Linear Coding to optimize the meaningful features from a high degree of freedom. It is connected to Support Vector Machines (SVM) for efficient classification. The experimental results show that our proposed approach is very efficient to classify the leaves which have similar color, and shape.

A Natural Scene Statistics Based Publication Classification Algorithm Using Support Vector Machine (서포트 벡터 머신을 이용한 자연 연상 통계 기반 저작물 식별 알고리즘)

  • Song, Hyewon;Kim, Doyoung;Lee, Sanghoon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.42 no.5
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    • pp.959-966
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    • 2017
  • Currently, the market of digital contents such as e-books, cartoons and webtoons is growing up, but the copyrights infringement are serious issue due to their distribution through illegal ways. However, the technologies for copyright protection are not developed enough. Therefore, in this paper, we propose the NSS-based publication classification method for copyright protection. Using histogram calculated by NSS, we propose classification method for digital contents using SVM. The proposed algorithm will be useful for copyright protection because it lets us distinguish illegal distributed digital contents more easily.

Digital Mapping Based on Digital Ortho Images (수치정사투영영상을 이용한 수치지도제작)

  • 이재기;박경식
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.18 no.1
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    • pp.1-9
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    • 2000
  • In the recent day, the necessity and the effective usage are increased rapidly, and it is applied in many other fields as well as in the field of ortho-photo map. In this study, we extract each objects on the aerial image and automatically classify graphic information to produce digital map using only digital ortho-image without particular drawing devices for producing digital map. For this purpose, we have applied a lot of the image processing techniques and fuzzy theory, classified outline and lane of road and building, and had each layer according to each feature. Especially, in the case of the building, the outer vector lines extracted by pixel unit at the building were very complex, but we have developed the program to be expressed by I-dimensional linear type between building corners. In the result of this study, we could not extract and recognize all of the object on the image all together, but we have got the error within 50cm using semi-automatic technique. Therefore, this method will be used effectively in producing 1/5,000 digital map.

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Development of Simulation Software for EEG Signal Accuracy Improvement (EEG 신호 정확도 향상을 위한 시뮬레이션 소프트웨어 개발)

  • Jeong, Haesung;Lee, Sangmin;Kwon, Jangwoo
    • Journal of rehabilitation welfare engineering & assistive technology
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    • v.10 no.3
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    • pp.221-228
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    • 2016
  • In this paper, we introduce our simulation software for EEG signal accuracy improvement. Users can check and train own EEG signal accuracy using our simulation software. Subjects were shown emotional imagination condition with landscape photography and logical imagination condition with a mathematical problem to subject. We use that EEG signal data, and apply Independent Component Analysis algorithm for noise removal. So we can have beta waves(${\beta}$, 14-30Hz) data through Band Pass Filter. We extract feature using Root Mean Square algorithm and That features are classified through Support Vector Machine. The classification result is 78.21% before EEG signal accuracy improvement training. but after successive training, the result is 91.67%. So user can improve own EEG signal accuracy using our simulation software. And we are expecting efficient use of BCI system based EEG signal.

Boundary Detection using Adaptive Bayesian Approach to Image Segmentation (적응적 베이즈 영상분할을 이용한 경계추출)

  • Kim Kee Tae;Choi Yoon Su;Kim Gi Hong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.22 no.3
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    • pp.303-309
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    • 2004
  • In this paper, an adaptive Bayesian approach to image segmentation was developed for boundary detection. Both image intensities and texture information were used for obtaining better quality of the image segmentation by using the C programming language. Fuzzy c-mean clustering was applied fer the conditional probability density function, and Gibbs random field model was used for the prior probability density function. To simply test the algorithm, a synthetic image (256$\times$256) with a set of low gray values (50, 100, 150 and 200) was created and normalized between 0 and 1 n double precision. Results have been presented that demonstrate the effectiveness of the algorithm in segmenting the synthetic image, resulting in more than 99% accuracy when noise characteristics are correctly modeled. The algorithm was applied to the Antarctic mosaic that was generated using 1963 Declassified Intelligence Satellite Photographs. The accuracy of the resulting vector map was estimated about 300-m.

A New Algorithm for the Interpretation of Joint Orientation Using Multistage Convergent Photographing Technique (수렴다중촬영기법을 이용한 새로운 절리방향 해석방법)

  • 김재동;김종훈
    • Tunnel and Underground Space
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    • v.13 no.6
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    • pp.486-494
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    • 2003
  • When the orientations of joints are measured on a rock exposure, there are frequent cases that are difficult to approach by the surveyor to the target joints or to set up scanlines on the slope. In this study, to complement such limit and weak points, a new algorithm was developed to interpret joint orientation from analyzing the images of rock slope. As a method of arranging the multiple images of a rock slope, the multistage convergent photographing system was introduced to overcome the limitation of photographing direction which existing method such as parallel stereophotogrammetric system has and to cover the range of image measurement, which is the overlapping area between the image pair, to a maximum extent. To determine camera parameters in the perspective projection equation that are the main elements of the analysis method, a new method was developed introducing three ground control points and single ground guide point. This method could be considered to be very simple compared with other existing methods using a number of ground control points and complicated analysis process. So the global coordinates of a specific point on a rock slope could be analyzed with this new method. The orientation of a joint could be calculated using the normal vector of the joint surface which can be derived from the global coordinates of several points on the joint surface analyzed from the images.

Stylized Specular Reflections Using Projective Textures based on Principal Curvature Analysis (주곡률 해석 기반의 투영 텍스처를 이용한 스타일 반사 효과)

  • Lee, Hwan-Jik;Choi, Jung-Ju
    • Journal of the HCI Society of Korea
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    • v.1 no.1
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    • pp.37-44
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    • 2006
  • Specular reflections provide the visual feedback that describes the material type of an object, its local shape, and lighting environment. In photorealistic rendering, there have been a number of research available to render specular reflections effectively based on a local reflection model. In traditional cel animations and cartoons, specular reflections plays important role in representing artistic intentions for an object and its related environment reflections, so the shapes of highlights are quite stylistic. In this paper, we present a method to render and control stylized specular reflections using projective textures based on principal curvature analysis. Specifying a texture as a pattern of a highlight and projecting the texture on the specular region of a given 3D model, we can obtain a stylized representation of specular reflections. For a given polygonal model, a view point, and a light source, we first find the maximum specular intensity point, and then locate the texture projector along the line parallel to the normal vector and passing through the point. The orientation of the projector is determined by the principal directions at the point. Finally, the size of the projection frustum is determined by the principal curvatures corresponding to the principal directions. The proposed method can control the position, orientation, and size of the specular reflection efficiently by translating the projector along the principal directions, rotating the projector about the normal vector, and scaling the principal curvatures, respectively. The method is be applicable to real-time applications such as cartoon style 3D games. We implement the method by Microsoft DirectX 9.0c SDK and programmable vertex/pixel shaders on Nvidia GeForce FX 7800 graphics subsystems. According to our experimental results, we can render and control the stylized specular reflections for a 3D model of several ten thousands of triangles in real-time.

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