• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.235-238
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• 2001

최근 효과적인 내용기반 영상검색을 위해 특징 추출 방법이 많이 연구되고 있다. 특히 칼라 정보를 이용하여 특징을 얻는 방법은 여러 가지 장점 때문에 많이 사용되고 있다 본 논문에서는 칼라 코렐로그램(color correlogram) 기반의 새로운 특징 추출 방법을 제안한다. 제안한 방법은 웨이브릿 변환 계수를 사용하여 영상을 복잡한 영역과 그렇지 않은 영역으로 분할하고, 각 영역의 칼라 코렐로그램을 영상의 특징으로 사용해 영상을 검색하는 방법이다. 제안한 방법으로 영상을 검색하는 방법은 기존의 칼라 코렐로그램을 이용한 방법보다 성능이 우수함을 실험에서 확인할 수 있었다.

• Proceedings of the Korea Multimedia Society Conference
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• 1998.04a
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• pp.28-33
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• 1998

대량의 영상데이터베이스에서 질의영상에 대한 유사영상을 검색할 때의 유사도 계산을 위한 시간소모는 영상의 실시간 검색효율을 저하시키는 요인이 된다. 본 논문에서는 키영상(key image)을 이용하여 영상데이터베이스의 각 영상과 키영상의 유사도를 미리 계산해 둠으로써 질의영상과 데이터베이스 영상간의 유사도 계산시간을 단축시킨다. 그리고 검색효율을 높이기 위해 1차적으로 칼라특징으로 유사영상들을 분류한 후, 1차 분류된 영상들만을 대상으로 계층적으로 질감특징값으로 영상을 비교함으로써 검색효율을 상승시킨다. Oracle 데이터베이스 상에서 본 계층적 내용기반 영상검색시스템을 구현하였다.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10b
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• pp.259-261
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• 1998

멀티미디어 데이터 중에서도 많은 부문의 응용에 사용되는 이미지 데이터의 내용 기반 검색에 대한 연구가 활발히 이뤄지고 있지만, 기조의 내용 기반 이미지 검색 대부분이 대상으로 삼고 있는 임지 포맷과는 달리 현재 이용되는 대부분의 이미지는 압축된 상태이다. 이미지 압축의 표준으로 사용되는 JPEG 압축 이미지에 대해서 압축 상태에서 특성을 추출하고 이를 검색에 이용하면 기존의 방법에 비해 압축을 해제하는 비용을 줄일 수 있고 블록 정보를 이용하는 장점을 가지게 된다. 본 논문에서는 JPEG 압축 이미지에서 블록 단위의 정보를 가진 특성으로 추출해내고 이를 사용한 이미지 검색 기법을 제안한다.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.12
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• pp.756-771
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• 2003

Digital Video Library System which manages a large amount of multimedia information requires efficient and effective retrieval methods. In this paper, we propose and implement a new video search and retrieval algorithm that compares the query video shot with the video shots in the archives in terms of foreground object, background image, audio, and its context. The foreground object is the region of the video image that has been changed in the successive frames of the shot, the background image is the remaining region of the video image, and the context is the relationship between the low-level features of the adjacent shots. Comparing these features is a result of reflecting the process of filming a moving picture, and it helps the user to submit a query focused on the desired features of the target video clips easily by adjusting their weights in the comparing process. Although the proposed search and retrieval algorithm could not totally reflect the high level semantics of the submitted query video, it tries to reflect the users' requirements as much as possible by considering the context of video clips and by adjusting its weight in the comparing process.

• Journal of Korea Multimedia Society
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• v.9 no.5
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• pp.658-670
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• 2006

As the educational media tends to be more digitalized and individualized, the learning paradigm is dramatically changing into e-learning. Existing on-line courseware gives a learner more chances to learn when they are home with their own PCs. However, it is of little use when they are away from their digital media. Also, it is very labor-intensive to convert the original off-line contents to on-line contents. This paper proposes education mobile contents(EMC) that can supply the learners with dynamic interactions using various multimedia information by recognizing real images of off-line contents using mobile devices. Content-based image retrieval based on object shapes is used to recognize the real image, and shapes are represented by differential chain code with estimated new starting points to obtain rotation-invariant representation, which is fitted to computational resources of mobile devices with low resolution camera. Moreover we use a dynamic time warping method to recognize the object shape, which compensates scale variations of an object. The EMC can provide learners with quick and accurate on-line contents on off-line ones using mobile devices without limitations of space.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.92-99
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• 2009

This paper established the range of the wavelength of traffic lights to detection the color of traffic lights and the color component segmentation with the range of the wavelength. Development of traffic light automatic discrimination system is consists of the color detection and the traffic lights recognition. In this thesis, it established the range of the wavelength of traffic lights to detection the color of traffic lights and the color segmentation with the range of the wavelength. By the segmentation, the traffic light colors(red, orange and green) can be detected and the background is changed into gray image. Next, we proposed the algorithm which can detect the area of traffic lights in the various surroundings with the wavelet transformation algorithm. Also, we proposed traffic lights recognition algorithm using between the edge operator and the Hausdorff distance algorithm based on CBIR(Content-based Image retrieval). Therefore, the proposed algorithm is more superior to the conventional algorithm by experimenting with the illumination including the traffic lights and the backgrounds with various images.

• Journal of the Korea Computer Industry Society
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• v.2 no.12
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• pp.1601-1608
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• 2001

Digital library is the most important database system that needs information retrieval engine for natural language documents and multimedia data. This paper describes the experimental results of information retrieval engine and browser based on natural language processing. It includes lexical analysis, syntax processing, stemming, and keyword indexing for the natural language text. With the experimental database ‘Earth and Space Science’ that has lots of images and titles and their descriptive text in natural language, text-based search engine was tested. Combined with content-based image search engine, it is expected to be a multimedia information retrieval system in digital library

• The KIPS Transactions:PartB
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• v.11B no.5
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• pp.581-586
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• 2004

In this paper, we proposed a content-based image retrieval using a color feature for central region and its optimized comparing bin method. Human's visual characteristic is influenced by existent of central object. So we supposed that object is centrally located in image and then we extract color feature at central region. When the background of image is simple, the retrieval result can be bad affected by major color of background. Our method overcome this drawback as a result of the human visual characteristic. After we transform Image into HSV color space, we extract color feature from the quantized image with 16 level. The experimental results showed that the method using the eight high rank bin is better than using the 16 bin The case which extracts the feature with image's central region was superior compare with the case which extracts the feature with the whole image about 5%.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.01a
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• pp.39-42
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• 2011

본 논문에서는 영상들의 특징들을 추출하여 특징 값들의 비교를 통하여 질의 영상의 유사 영상을 검색하는 방법을 제안한다. 제안하는 방법은 입력 영상들의 색상 히스토그램으로 색상 특징 값들을 추출하고 질감 정보인 에지 정보와 이웃화소간의 공간 관계를 분석하여 질감 특징 값들을 추출하여 저장한 후 질의 이미지의 색상과 질감 특징들을 구하여 비교를 통하여 유사도를 분석하고 결과 영상을 보여준다. 또한 색상과 질감을 혼합하여 사용할 때 적응적으로 가중치를 부여함으로써 가중치가 적합하지 않아 발생하는 오 검출될 현상을 피할 수 있게 되었다. 실험을 통하여 기존의 방법과의 성능을 비교분석하였고 본 방법의 우수성을 입증하였다.

• Speech Sciences
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• v.12 no.1
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• pp.135-142
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• 2005

An important aspect of video indexing is the ability to segment video into meaningful segments, i.e., content-based video segmentation. Since the audio signal in the sound track is synchronized with image sequences in the video program, a speech signal in the sound track can be used to segment video into meaningful segments. In this paper, we propose a new approach to content-based video segmentation. This approach uses closed caption to construct a recognition network for speech recognition. Accurate time information for video segmentation is then obtained from the speech recognition process. For the video segmentation experiment for TV news programs, we made 56 video summaries successfully from 57 TV news stories. It demonstrates that the proposed scheme is very promising for content-based video segmentation.