• Journal of Digital Convergence
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• v.11 no.12
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• pp.459-465
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• 2013

This paper is a study on an object extraction method which using color features of an object and background in the image. A human recognizes an object through the color difference of object and background in the image. So we must to emphasize the color's difference that apply to extraction result in this image. Therefore, we have converted to HSV color images which similar to human visual system from original RGB images, and have created two each other images that applied Median Filter and we merged two Median filtered images. And we have applied the Mean Shift algorithm which a data clustering method for clustering color features. Finally, we have normalized 3 image channels to 1 image channel for binarization process. And we have created object map through the binarization which using average value of whole pixels as a threshold. Then, have extracted major object from original image use that object map.

• Korean Journal of Remote Sensing
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• v.27 no.4
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• pp.421-433
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• 2011

The importance of acquisition of road information has recently been increased with a rapid growth of spatial-related services such as urban information system and location based service. This paper proposes an automatic road extraction method using object-based approach which was issued alternative of pixel-based method recently. Firstly, the spatial objects were created by MSRS(Modified Seeded Region Growing) method, and then the key road objects were extracted by using properties of objects such as their shape feature information and adjacency. The omitted road objects were also traced considering spatial correlation between extracted road and their neighboring objects. In the end, the final road region was extracted by connecting discontinuous road sections and improving road surfaces through their geometric properties. To assess the proposed method, quantitative analysis was carried out. From the experiments, the proposed method generally showed high road detection accuracy and had a great potential for the road extraction from high resolution satellite images.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.6
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• pp.712-717
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• 2003

A novel multi-snake is proposed for efficient extraction of multi-object contours from a natural scene. An NTGST(noise-tolerant generalized symmetry transform) is used as a context-free attention operator to detect and locate multiple objects from a complex background and then the snake points are automatically initialized nearby the contour of each detected object using symmetry map of the NTGST before multiple snakes are introduced. These procedures solve the knotty subjects of automatic snake initialization and simultaneous extraction of multi-object contours in conventional snake algorithms. Because the snake points are initialized nearby the actual contour of each object, as close as possible, contours with high convexity and/or concavity can be easily extracted. The experimental results show that the proposed method can efficiently extract multi-object contours from a noisy and complex background of natural scenes.

• The KIPS Transactions:PartB
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• v.17B no.5
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• pp.375-380
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• 2010

Most of previous algorithms of object boundary extraction have been studied for extracting the boundary of single object. However, multiple objects are much common in the real image. The proposed algorithm of extracting the boundary of each of multiple objects has two steps. In the first step, we propose the fast method using the outer and inner products; the initial contour including multiple objects is split and connected and each of new contours includes only one object. In the second step, an improved active contour model is studied to extract the boundary of each object included each of contours. Experimental results with various test images have shown that our algorithm produces much better results than the previous algorithms.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1243-1248
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• 2006

Object tracking in a real time image is one of interesting subjects in computer vision and many practical application fields past couple of years. But sometimes existing systems cannot find object by recognize background noise as object. This paper proposes a method of object detection and tracking using adaptive background image in real time. To detect object which does not influenced by illumination and remove noise in background image, this system generates adaptive background image by real time background image updating. This system detects object using the difference between background image and input image from camera. After setting up MBR(minimum bounding rectangle) using the internal point of detected object, the system tracks object through this MBR. In addition, this paper evaluates the test result about performance of proposed method as compared with existing tracking algorithm.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.2
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• pp.48-55
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• 2008

In this paper we propose a novel method for image retrieval system using image segmentation and salient points. The proposed method consists of four steps. In the first step, images are segmented into several regions by JSEG algorithm. In the second step, for the segmented regions, dominant colors and the corresponding color histogram are constructed. By using dominant colors and color histogram, we identify candidate regions where objects may exist. In the third step, real object regions are detected from candidate regions by SIFT matching. In the final step, we measure the similarity between the query image and DB image by using the color correlogram technique. Color correlogram is computed in the query image and object region of DB image. By experimental results, it has been shown that the proposed method detects multi-object very well and it provides better retrieval performance compared with object-based retrieval systems.

• Journal of Korea Multimedia Society
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• v.5 no.3
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• pp.272-280
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• 2002

In this paper, we present a method to extract a moving object and to measure the distance to it by using the stereo vision system. The moving factor is to be extracted through a match of a pixel unit for the moving object where the adaptive threshold is effectively dealt with to remove changes in the brightness of the image. The distance to moving object is measured by using a stereo vision system which employs a parallel camera. The experimental results show that the proposed algorithm could be effectively applied to distance measurement to moving object because it has an average error of one percent.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06b
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• pp.361-363
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• 2006

객체 기반의 3차원 입체 변환 기법은 연속적으로 입력되는 2D 동영상에서 객체를 추출하여 입체 영상으로 변환하는 기법을 말한다. 두 눈에 투시되는 각 객체마다 서로 다른 시차를 가져야 입체감을 느낄 수 있다. 따라서 2D 영상에서 정확한 객체를 추출하는 것이 중요하다. 본 논문에서는 프레임간의 차이를 이용하여 대략의 움직이는 객체 영역을 얻고, 그래프 및 알고리즘을 사용하여 정확하고 안정적인 객체를 자동으로 추출한다. 스크린과 양안 사이의 거리를 고려하여 입체 영상을 만들어 낸다. 후처리 단계에서는 입체 영상을 만들어 내면서 생긴 빈 공간을 채운다. 실험에서는 2D 영상으로부터 입체 영상을 생성한 것을 보여 준다.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10a
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• pp.136-138
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• 2000

대용량의 멀티미디어 자료를 기반으로 하는 산업의 급성장은 이에 적합한 효율적인 저장 및 검색시스템을 요구하고 있다. 그러나, 멀티미디어 자료의 고차원적인 특성은 저장과 검색에 있어 성능을 저하시키는 문제점으로 지적되고 있다. 이를 해결하기 위하여 멀티미디어 자료로부터 저차원의 특성을 추출하여 내용기반 검색을 수행하는 연구가 진행되어오고 있다. 본 논문에서는 이미지내의 객체 MBR(Minimum Bounding Rectangle)을 이용하여 저차원의 색상정보와 모양정보를 추출하는 기법을 제안한다. 히스토그램정보는 이미지의 객체를 포함하는 MBR을 이용하여 9개의 타일로 균등분할하여 추출하며, 모양정보는 객체 MBR의 중심으로부터 16방향의 스캐닝을 통해 16개의 점으로 구성된 모양정보를 추출한다. 실험을 통하여 추출된 정보의 검색성능을 평가하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1326-1329
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• 2015

최근 들어 공간 지식을 활용한 다양한 서비스들이 개발됨에 따라, 공간 객체들 간의 정성적 공간 관계를 표현한 정성 공간 지식의 수요가 크게 늘어나고 있다. 공간 객체 각각의 세부 정보를 담은 대용량의 공간 데이터들은 개방화가 점차 확대되고 있으나, 공간 객체들 간의 정성적 관계를 표현한 정성 공간 지식은 상대적으로 확보하기 어려운 실정이다. 본 논문에서는 하둡 맵리듀스 병렬 분산 컴퓨터 환경을 이용해, 대용량의 공간 데이터로부터 공간 객체들 간의 위상 관계와 방향 관계를 나타내는 정성 공간 지식을 자동으로 추출하는 공간 지식 추출기를 제안한다. 본 논문에서 제안하는 대용량의 공간 지식 추출기는 맵리듀스 프레임워크를 기반으로 R-트리 색인과 범위 질의들을 효과적으로 이용함으로써, 웹 스케일 수준의 정성 공간 지식을 매우 효율적으로 추출해낸다. Open Street Map (OSM) 공개 데이터를 이용한 성능 분석 실험을 통해, 본 논문에서 제안하는 대용량 공간 지식 추출기의 높은 성능을 확인할 수 있었다.