• 제목/요약/키워드: Automatic Extraction Algorithm

검색결과 296건 처리시간 0.03초

Quadtree와 영역확장법에 의한 LiDAR 데이터의 지면점 추출 (Extraction of Ground Points from LiDAR Data using Quadtree and Region Growing Method)

  • 배대섭;김진남;조기성
    • 대한공간정보학회지
    • /
    • 제19권3호
    • /
    • pp.41-47
    • /
    • 2011
  • 원시 LiDAR 데이터는 벡터 구조이기 때문에 직접 활용 시 처리과정이 복잡해지지만, LiDAR 데이터를 필터링을 통해 정규 가상 격자 형태로 변환하면 데이터 용량이 감소되고 처리 속도가 빠르기 때문에 저가의 장비에서도 처리가 가능하다. 특히 Quadtree와 같은 영상 압축 처리 기법을 적용할 경우, 평활화를 통하여 비지면 요소인 자동차, 수목등이 제거되어 모델링에 유리하다는 장점이 있다. 따라서 본 연구에서는 대용량의 LiDAR 데이터로부터 Quadtree와 영역확장법을 활용하여 지면점을 자동 추출할 수 있는 알고리즘을 제시하였으며, 오차분류기법을 활용하여 정확도를 분석하였다. 그 결과, 지면점 분류 정확도는 98%이상으로 나타나, 지면점 추출에 유리함을 알 수 있었다. 또한 Quadtree와 영역확장법을 활용시 자동차, 수목등의 비지면 요소들을 효과적으로 제거할 수 있었다.

영상 매칭으로 생성된 DSM을 이용한 반자동 3차원 건물 외곽선 추출 기법 개발 (Semi-automatic Extraction of 3D Building Boundary Using DSM from Stereo Images Matching)

  • 김수현;이수암
    • 대한원격탐사학회지
    • /
    • 제34권6_1호
    • /
    • pp.1067-1087
    • /
    • 2018
  • 기존의 LiDAR 자료 기반의 건물 외곽선 추출 연구에서는 고정밀 포인트클라우드를 사용하여 자동으로 건물 지붕 영역을 분류하고 이를 입력자료로 하여 건물 외곽선을 추출했다. 반면에 스테레오 영상 정합을 통해 생성된 DSM은 고정밀 포인트클라우드 자료와 달리 원시 자료인 포인트클라우드에 잡음과 비어있는 격자가 존재하기 때문에 완전한 자동으로 건물 지붕 영역을 분류하는데 어려움이 있다. 따라서 본 논문에서는 스테레오 영상 정합을 통해 생성된 DSM에 사용자 입력을 통한 watershed segmentation 기법을 적용하여 반자동으로 건물의 3차원 외곽선을 추출하는 기법을 제안한다. 제안된 기법은 DSM 내 건물 영역을 표시하는 단순한 마커 정보만을 입력하기 때문에 사용자 입력을 최소화한 방식으로 건물의 3차원 외곽선을 생성할 수 있다.

가음단층계의 선형구조 추출과 선형구조와 단층활동의 관련성 (Extraction of Lineament and Its Relationship with Fault Activation in the Gaeum Fault System)

  • 오정식
    • 한국지형학회지
    • /
    • 제26권2호
    • /
    • pp.69-84
    • /
    • 2019
  • The purpose of this study is to extract lineaments in the southeastern part of the Gaeum Fault System, and to understand their characteristics and a relationship between them and fault activation. The lineaments were extracted using a multi-layered analysis based on a digital elevation model (5 m resolution), aerial photos, and satellite images. First-grade lineaments inferred as an high-activity along them were classified based on the displacement of the Quaternary deposits and the distribution of fault-related landforms. The results of classifying the first-grade lineaments were verified by fieldwork and electrical resistivity survey. In the study area of 510 km2, a total of 222 lineaments was identified, and their total length was 333.4 km. Six grade lineaments were identified, and their total length was 11.2 km. The lineaments showed high-density distribution in the region along the Geumcheon, Gaeum, Ubo fault, and a boundary of the Hwasan cauldron consisting the Gaeum Fault System. They generally have WNW-ESE trend, which is the same direction with the strike of Gaeum Fault System. Electrical resistivity survey was conducted on eight survey lines crossing the first-grade lineament. A low-resistivity zone, which is assumed to be a fault damage zone, has been identified across almost all survey lines (except for only one survey line). The visual (naked eyes) detecting of the lineament was evaluated to be less objectivity than the automatic extraction using the algorithm. However, the results of electrical resistivity survey showed that first-grade lineament extracted by visual detecting was 83% reliable for inferred fault detection. These results showed that objective visual detection results can be derived from multi-layered analysis based on tectonic geomorphology.

회색도 변환 행렬 특징과 SVM을 이용한 흑색종 분류 알고리즘 (Melanoma Classification Algorithm using Gray-level Conversion Matrix Feature and Support Vector Machine)

  • 구정모;나승대;조진호;김명남
    • 한국멀티미디어학회논문지
    • /
    • 제21권2호
    • /
    • pp.130-137
    • /
    • 2018
  • Recently, human life is getting longer due to change of living environment and development of medical technology, and silver medical technology has been in the limelight. Geriatric skin disease is difficult to detect early, and when it is missed, it becomes a malignant disease and is difficult to treatment. Melanoma is one of the most common diseases of geriatric skin disease and initially has a similar modality with the nevus. In order to overcome this problem, we attempted to perform a feature analysis in order to attempt automatic detection of melanoma-like lesions. In this paper, one is first order analysis using information of pixels in radiomic feature. The other is a gray-level co-occurrence matrix and a gray level run length matrix, which are feature extraction methods for converting image information into a matrix. The features were extracted through these analyses. And classification is implemented by SVM.

Recognition of the Passport by Using Fuzzy Binarization and Enhanced Fuzzy Neural Networks

  • Kim, Kwang-Baek
    • 한국지능시스템학회:학술대회논문집
    • /
    • 한국퍼지및지능시스템학회 2003년도 ISIS 2003
    • /
    • pp.603-607
    • /
    • 2003
  • The judgment of forged passports plays an important role in the immigration control system, for which the automatic and accurate processing is required because of the rapid increase of travelers. So, as the preprocessing phase for the judgment of forged passports, this paper proposed the novel method for the recognition of passport based on the fuzzy binarization and the fuzzy RBF neural network newly proposed. first, for the extraction of individual codes being recognized, the paper extracts code sequence blocks including individual codes by applying the Sobel masking, the horizontal smearing and the contour tracking algorithm in turn to the passport image, binarizes the extracted blocks by using the fuzzy binarization based on the membership function of trapezoid type, and, as the last step, recovers and extracts individual codes from the binarized areas by applying the CDM masking and the vertical smearing. Next, the paper proposed the enhanced fuzzy RBF neural network that adapts the enhanced fuzzy ART network to the middle layer and applied to the recognition of individual codes. The results of the experiment for performance evaluation on the real passport images showed that the proposed method in the paper has the improved performance in the recognition of passport.

  • PDF

레이저 트랙커(Leica LTD 500)를 이용한 로봇 성능 평가 시스템 개발 (Development of a Robot Performance Evaluation System Using Leica LTD 500 Laser Tracker)

  • 김미경;윤천석;강희준;서영수;노영식;손홍래
    • 한국정밀공학회:학술대회논문집
    • /
    • 한국정밀공학회 2005년도 춘계학술대회 논문집
    • /
    • pp.1001-1006
    • /
    • 2005
  • A Robot Performance Evaluation System(RPES) with the laser tracker Leica LTD 500 was developed according to the ISO 9283 robot performance criteria. The developed system is set up a test robot to continuously move the prescribed cyclic trajectories without a human intervention and the laser tracker to simultaneously measure the robot's movement. And then, the system automatically extracts the required data from the tremendous measured data, and computes the various performance criteria which represents the present state of the test robot's performance. This paper explains how ISO 9283 robot performance criteria was used for the developed system, and suggests a automatic data extraction algorithm from the mass of measured data. And also, a user-friendly Robot Performance Evaluation System(RPES) Software was developed with Visual Basic satisfying the need of Hyundai Motor Company. The developed system was implemented on NACHI 8608 AM 11 robot. The resulted output shows the effectiveness of the developed system.

  • PDF

칼라 나사 검사를 위한 표면 영역 자동 검출 (Seoul National University of Science and Technology)

  • 송태훈;하종은
    • 한국전자통신학회논문지
    • /
    • 제11권1호
    • /
    • pp.107-112
    • /
    • 2016
  • 나사는 산업의 모든 분야에서 널리 사용되는 중요한 부품이다. 최근에는 여러 가지 필요에 의해 다양한 칼라 나사가 출시되고 있다. 이에 따라 제조 공정상에서 실시간 품질 검사가 요구되고 있다. 본 논문에서는 칼라 정보와 동적 계획법(Dynamic Programming) 알고리듬을 이용한 칼라 나사 검사를 위한 표면 영역 자동 추출 알고리듬에 대해 다루도록 한다. 나사의 외곽 경계는 칼라 성분의 차이를 이용하여 보다 강인한 검출이 가능하도록 한다. 나사의 내부 경계는 직교 좌표계를 극좌표계로 변환후 흑백 이미지상에서 일정 영역의 밝기값 차이를 이용한 동적 계획법을 적용하여 추출하도록 한다. 실험에서는 동일한 인자값을 이용한 결과를 분석하도록 한다.

Passport Recognition using Fuzzy Binarization and Enhanced Fuzzy RBF Network

  • Kim, Kwang-Baek
    • 한국지능시스템학회논문지
    • /
    • 제14권2호
    • /
    • pp.222-227
    • /
    • 2004
  • Today, an automatic and accurate processing using computer is essential because of the rapid increase of travelers. The determination of forged passports plays an important role in the immigration control system. Hence, as the preprocessing phase for the determination of forged passports, this paper proposes a novel method for the recognition of passports based on the fuzzy binarization and the fuzzy RBF network. First, for the extraction of individual codes for recognizing, this paper targets code sequence blocks including individual codes by applying Sobel masking, horizontal smearing and a contour tracking algorithm on the passport image. Then the proposed method binarizes the extracted blocks using fuzzy binarization based on the trapezoid type membership function. Then, as the last step, individual codes are recovered and extracted from the binarized areas by applying CDM masking and vertical smearing. This paper also proposes an enhanced fuzzy RBF network that adapts the enhanced fuzzy ART network for the middle layer. This network is applied to the recognition of individual codes. The results of the experiments for performance evaluation on the real passport images showed that the proposed method has the better performance compared with other approaches.

Baggage Recognition in Occluded Environment using Boosting Technique

  • Khanam, Tahmina;Deb, Kaushik
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • 제11권11호
    • /
    • pp.5436-5458
    • /
    • 2017
  • Automatic Video Surveillance System (AVSS) has become important to computer vision researchers as crime has increased in the twenty-first century. As a new branch of AVSS, baggage detection has a wide area of security applications. Some of them are, detecting baggage in baggage restricted super shop, detecting unclaimed baggage in public space etc. However, in this paper, a detection & classification framework of baggage is proposed. Initially, background subtraction is performed instead of sliding window approach to speed up the system and HSI model is used to deal with different illumination conditions. Then, a model is introduced to overcome shadow effect. Then, occlusion of objects is detected using proposed mirroring algorithm to track individual objects. Extraction of rotational signal descriptor (SP-RSD-HOG) with support plane from Region of Interest (ROI) add rotation invariance nature in HOG. Finally, dynamic human body parameter setting approach enables the system to detect & classify single or multiple pieces of carried baggage even if some portions of human are absent. In baggage detection, a strong classifier is generated by boosting similarity measure based multi layer Support Vector Machine (SVM)s into HOG based SVM. This boosting technique has been used to deal with various texture patterns of baggage. Experimental results have discovered the system satisfactorily accurate and faster comparative to other alternatives.

이동카메라 환경에서의 에지 세그먼트 정합을 통한 이동물체 검출 (Moving Object Detection with Rotating Camera Based on Edge Segment Matching)

  • 이준형;채옥삼
    • 한국컴퓨터정보학회논문지
    • /
    • 제13권6호
    • /
    • pp.1-12
    • /
    • 2008
  • 본 논문에서는 카메라 회전에 의한 배경의 왜곡이 존재하는 환경에서 조명변화와 대상물체의 흔들림에도 강건한 에지 세그먼트 정합을 통한 이동물체 자동 검출방법을 제안한다. 이동물체 검출을 위한 기존의 연구는 카메라가 고정되어 있는 환경을 대상으로 한 연구가 주를 이루지만 응용분야의 확대로 카메라를 회전함으로써 하나의 카메라로 보다 넓은 영역을 커버할 수 있는 시스템에 대한 요구가 커지고 있다. 본 연구에서는 왜곡이 적은 에지세그먼트 기반 배경 파노라마 영상 생성 방안, 왜곡이 포함된 파노라마 영상에서 신속하게 현재 영상의 배경에지영상을 추출할 수 있는 에지특징 기반 GHT를 이용한 배경영상생성 방안, 시점의 차이와 왜곡을 극복하고 신뢰성 있게 이동 에지 세그먼트를 추출할 수 있는 에지 정합방안을 제안한다. 실험결과 제안한 방법은 조명 변화와 카메라의 흔들림에도 정확한 이동물체 검출이 가능함이 입증되었다.

  • PDF