• 제목/요약/키워드: Image features

검색결과 3,385건 처리시간 0.045초

Managing and Modeling Strategy of Geo-features in Web-based 3D GIS

  • Kim, Kyong-Ho;Choe, Seung-Keol;Lee, Jong-Hun;Yang, Young-Kyu
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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    • pp.75-79
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    • 1999
  • Geo-features play a key role in object-oriented or feature-based geo-processing system. So the strategy for how-to-model and how-to-manage the geo-features builds the main architecture of the entire system and also supports the efficiency and functionality of the system. Unlike the conventional 2D geo-processing system, geo-features in 3B GIS have lots to be considered to model regarding the efficient manipulation and analysis and visualization. When the system is running on the Web, it should also be considered that how to leverage the level of detail and the level of automation of modeling in addition to the support for client side data interoperability. We built a set of 3D geo-features, and each geo-feature contains a set of aspatial data and 3D geo-primitives. The 3D geo-primitives contain the fundamental modeling data such as the height of building and the burial depth of gas pipeline. We separated the additional modeling data on the geometry and appearance of the model from the fundamental modeling data to make the table in database more concise and to allow the users more freedom to represent the geo-object. To get the users to build and exchange their own data, we devised a file format called VGFF 2.0 which stands for Virtual GIS File Format. It is to describe the three dimensional geo-information in XML(eXtensible Markup Language). The DTD(Document Type Definition) of VGFF 2.0 is parsed using the DOM(Document Object Model). We also developed the authoring tools for. users can make their own 3D geo-features and model and save the data to VGFF 2.0 format. We are now expecting the VGFF 2.0 evolve to the 3D version of SVG(Scalable Vector Graphics) especially for 3D GIS on the Web.

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Managing Scheme for 3-dimensional Geo-features using XML

  • Kim, Kyong-Ho;Choe, Seung-Keol;Lee, Jong-Hun;Yang, Young-Kyu
    • 한국GIS학회:학술대회논문집
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    • 한국GIS학회 1999년도 추계학술대회 발표요약문
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    • pp.47-51
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    • 1999
  • Geo-features play a key role in object-oriented or feature-based geo-processing system. So the strategy for how-to-model and how-to-manage the geo-features builds the main architecture of the entire system and also supports the efficiency and functionality of the system. Unlike the conventional 2D geo-processing system, geo-features in 3D GIS have lots to be considered to model regarding the efficient manipulation and analysis and visualization. When the system is running on the Web, it should also be considered that how to leverage the level of detail and the level of automation of modeling in addition to the support for client side data interoperability. We built a set of 3D geo-features, and each geo-feature contains a set of aspatial data and 3D geo-primitives. The 3D geo-primitives contain the fundamental modeling data such as the height of building and the burial depth of gas pipeline. We separated the additional modeling data on the geometry and appearance of the model from the fundamental modeling data to make the table in database more concise and to allow the users more freedom to represent the geo-object. To get the users to build and exchange their own data, we devised a fie format called VGFF 2.0 which stands for Virtual GIS File Format. It is to describe the three dimensional geo-information in XML(extensible Markup Language). The DTD(Document Type Definition) of VGFF 2.0 is parsed using the DOM(Document Object Model). We also developed the authoring tools for users can make their own 3D geo-features and model and save the data to VGFF 2.0 format. We are now expecting the VGFF 2.0 evolve to the 3D version of SVG(Scalable Vector Graphics) especially for 3D GIS on the Web.

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자연영상에서 한글 및 영문자의 구조적 특징을 이용한 문자영역 검출 (Character Region Detection Using Structural Features of Hangul & English Characters in Natural Image)

  • 오명관;박종천
    • 한국산학기술학회논문지
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    • 제15권3호
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    • pp.1718-1723
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    • 2014
  • 본 논문은 한글 및 영문자의 구조적 특징을 이용하여 자연영상에서 문자영역을 검출하는 기법을 제안하였다. 자연 영상에서 에지 특징 값을 추출하고 추출된 특징 값은 필터링을 수행하여 문자의 특징에 맞지 않는 특징 값을 제거하여 문자영역 후보를 선정한다. 선정된 문자영역 후보는 한글 자소 병합 알고리즘으로 하나의 문자로 병합하여 후보 문자영역으로 검출하고, 한글 문자 유형 판별 알고리즘으로 한글 문자영역 여부를 판별함으로서 한글 문자영역을 검출하고, 영문자는 영문자 에지 특징 값을 적용하여 영문자 영역을 검출한다. 실험결과, 복잡한 배경을 갖고 다양한 환경에서 촬영된 영상에서 한글 및 영문자 영역을 효과적으로 검출하였고, 제안한 문자영역 검출 방법은 향상된 검출 결과를 보여 주었다.

EDMFEN: Edge detection-based multi-scale feature enhancement Network for low-light image enhancement

  • Canlin Li;Shun Song;Pengcheng Gao;Wei Huang;Lihua Bi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제18권4호
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    • pp.980-997
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    • 2024
  • To improve the brightness of images and reveal hidden information in dark areas is the main objective of low-light image enhancement (LLIE). LLIE methods based on deep learning show good performance. However, there are some limitations to these methods, such as the complex network model requires highly configurable environments, and deficient enhancement of edge details leads to blurring of the target content. Single-scale feature extraction results in the insufficient recovery of the hidden content of the enhanced images. This paper proposed an edge detection-based multi-scale feature enhancement network for LLIE (EDMFEN). To reduce the loss of edge details in the enhanced images, an edge extraction module consisting of a Sobel operator is introduced to obtain edge information by computing gradients of images. In addition, a multi-scale feature enhancement module (MSFEM) consisting of multi-scale feature extraction block (MSFEB) and a spatial attention mechanism is proposed to thoroughly recover the hidden content of the enhanced images and obtain richer features. Since the fused features may contain some useless information, the MSFEB is introduced so as to obtain the image features with different perceptual fields. To use the multi-scale features more effectively, a spatial attention mechanism module is used to retain the key features and improve the model performance after fusing multi-scale features. Experimental results on two datasets and five baseline datasets show that EDMFEN has good performance when compared with the stateof-the-art LLIE methods.

그레이스케일 히스토그램을 이용한 에지의 수평 정보획득 영상검색 (Gray scale image histogram using the horizontal edge information search)

  • 정일회;박종안
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 2008년도 춘계종합학술대회 A
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    • pp.151-154
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    • 2008
  • 본 논문은 현 검색시스템의 단순한 키워드 입력 방식에서 발생하는 오차를 줄이기 위해 이미지의 그레이스케일 히스토그램과 에지정보를 이용하는 검색 시스템 구현을 하였다. 검색알고리즘은 질의 이미지의 특징을 추출하는 단계, 이미지 정제 및 에지정보 추출단계, 추출된 특징을 분석하는 단계, 분석된 특징들로부터 필요한 정보를 확보하는 단계, 확보된 정보를 데이터베이스로부터 검색하는 단계, 검색된 데이터베이스에서 이미지를 비교 추출단계로 이루어진다. 제안한 검색시스템은 빠른 검색과 고 정확도를 목적으로 실현되며 시뮬레이션을 통해 이를 검증하고자 하였다.

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A Study on the Emotional Evaluation of fabric Color Patterns

  • Koo, Hyun-Jin;Kang, Bok-Choon;Um, Jin-Sup;Lee, Joon-Whan
    • 감성과학
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    • 제5권3호
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    • pp.11-20
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    • 2002
  • There are Two new models developed for objective evaluation of fabric color patterns by applying a multiple regression analysis and an adaptive foray-rule-based system. The physical features of fabric color patterns are extracted through digital image processing and the emotional features are collected based on the psychological experiments of Soen[3, 4]. The principle physical features are hue, saturation, intensity and the texture of color patterns. The emotional features arc represented thirteen pairs of adverse adjectives. The multiple regression analyses and the adaptive fuzzy system are used as a tool to analyze the relations between physical and emotional features. As a result, both of the proposed models show competent performance for the approximation and the similar linguistic interpretation to the Soen's psychological experiments.

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특징들의 공유에 의한 기울어진 얼굴 검출 (Rotated face detection based on sharing features)

  • 송영모;고윤호
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2009년도 정보 및 제어 심포지움 논문집
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    • pp.31-33
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    • 2009
  • Face detection using AdaBoost algorithm is capable of processing images rapidly while having high detection rates. It seemed to be the fastest and the most robust and it is still today. Many improvements or extensions of this method have been proposed. However, previous approaches only deal with upright faces. They suffer from limited discriminant capability for rotated faces as these methods apply the same features for both upright and rotated faces. To solve this problem, it is necessary that we rotate input images or make independently trained detectors. However, this can be slow and can require a lot of training data, since each classifier requires the computation of many different image features. This paper proposes a robust algorithm for finding rotated faces within an image. It reduces the computational and sample complexity, by finding common features that can be shared across the classes. And it will be able to apply with multi-class object detection.

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컴퓨터 시각을 이용한 버얼리종 건조 잎 담배의 등급판별 가능성 (Feasibility in Grading the Burley Type Dried Tobacco Leaf Using Computer Vision)

  • 조한근;백국현
    • Journal of Biosystems Engineering
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    • 제22권1호
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    • pp.30-40
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    • 1997
  • A computer vision system was built to automatically grade the leaf tobacco. A color image processing algorithm was developed to extract shape, color and texture features. An improved back propagation algorithm in an artificial neural network was applied to grade the Burley type dried leaf tobacco. The success rate of grading in three-grade classification(1, 3, 5) was higher than the rate of grading in six-grade classification(1, 2, 3, 4, 5, off), on the average success rate of both the twenty-five local pixel-set and the sixteen local pixel-set. And, the average grading success rate using both shape and color features was higher than the rate using shape, color and texture features. Thus, the texture feature obtained by the spatial gray level dependence method was found not to be important in grading leaf tobacco. Grading according to the shape, color and texture features obtained by machine vision system seemed to be inadequate for replacing manual grading of Burely type dried leaf tobacco.

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또다른 접근방식에 의한 스테레오 정합 - 특정 값의 퍼지화 (Another Approach to Stereo Matching - Fuzzification of Feature Values)

  • 김동현;최우영;박래홍
    • 전자공학회논문지B
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    • 제28B권11호
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    • pp.925-933
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    • 1991
  • Conventional stereo matching techniques are based on the assumption that the features representing an object in left and right images have fixed attribute values. But, in fact, such features may take different values due to the practical stereo image formation and the image acquisition error, and thus the conventional techniques tend to result in the in the incorrect matching of features. In this paper, we propose a stereo matching mathod with a possibilistic view which copes with the possible variability of feature values. As a result, this method decreases the number of incorrect matching features when the values of corresponding features are somewhat large. The effectiveness of the proposed method is shown via computer simulation.

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Thermal Image Mosaicking Using Optimized FAST Algorithm

  • Nguyen, Truong Linh;Han, Dong Yeob
    • 한국측량학회지
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    • 제35권1호
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    • pp.41-53
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    • 2017
  • A thermal camera is used to obtain thermal information of a certain area. However, it is difficult to depict all the information of an area in an individual thermal image. To form a high-resolution panoramic thermal image, we propose an optimized FAST (feature from accelerated segment test) algorithm to combine two or more images of the same scene. The FAST is an accurate and fast algorithm that yields good positional accuracy and high point reliability; however, the major limitation of a FAST detector is that multiple features are detected adjacent to one another and the interest points cannot be obtained under no significant difference in thermal images. Our proposed algorithm not only detects the features in thermal images easily, but also takes advantage of the speed of the FAST algorithm. Quantitative evaluation shows that our proposed technique is time-efficient and accurate. Finally, we create a mosaic of the video to analyze a comprehensive view of the scene.