• Journal of Ubiquitous Convergence Technology
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• 제1권1호
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• pp.18-22
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• 2007

Multi-Instance Learning(MIL) performs well to deal with inherently ambiguity of images in multimedia retrieval. In this paper, an effective framework for Contented-Based Image Retrieval(CBIR) with MIL techniques is proposed, the effective mechanism is based on the image segmentation employing improved Mean Shift algorithm, and processes the segmentation results utilizing mathematical morphology, where the goal is to detect the semantic concepts contained in the query. Every sub-image detected is represented as a multiple features vector which is regarded as an instance. Each image is produced to a bag comprised of a flexible number of instances. And we apply a few number of MIL algorithms in this framework to perform the retrieval. Extensive experimental results illustrate the excellent performance in comparison with the existing methods of CBIR with MIL.

• Journal of information and communication convergence engineering
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• 제2권2호
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• pp.123-127
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• 2004

The most popular technique for image retrieval in a heterogeneous collection of color images is the comparison of images based on their color histogram. The color histogram describes the distribution of colors in the color space of a color image. In the most image retrieval systems, the color histogram is used to compute similarities between the query image and all the images in a database. But, small changes in the resolution, scaling, and illumination may cause important modifications of the color histogram, and so two color images may be considered to be very different from each other even though they have completely related semantics. A new method of color feature representation based on the 3-dimensional RGB color map is proposed to improve the defects of the color histogram. The proposed method is based on the three 2-dimensional projection map evaluated by projecting the RGB color space on the RG, GB, and BR surfaces. The experimental results reveal that the proposed is less sensitive to small changes in the scene and that achieve higher retrieval performances than the traditional color histogram.

• 반도체디스플레이기술학회지
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• 제7권2호
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• pp.69-76
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• 2008

Recently, as the multimedia processing application increases rapidly by going on increasing multimedia data, the efficient retrieval method of image information is required in many fields of application and becoming the matter of major concern. Furthermore, in the last few years rapid improvements in hardware technology have made it possible to process, store and retrieve huge amounts of data in a multimedia format. As a result, Content-Based Image Retrieval (CBIR) has been receiving widespread interest during the last decade. This paper propose the content-based retrieval system as a method for performing image retrieval through the effective feature analysis of the object of significant meaning by using YCbCr channel merging on the basis of the characteristics of man's visual system.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅲ
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• pp.1515-1518
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• 2003

This paper suggests the condensed two-stage retrieval method for fast image retrieval in the content-based image retrieval system, and proves the validity of the performance. The condensed two-stage retrieval method reduces the overall response time remarkably while it maintains relevance with the conventional exhaustive search method. It is explained by properties of the Cauchy-Schwartz inequality. In experimental result, it turns out that there is an optimal value of condensation ratio which minimizes the overall response time. We analyze the optimal condensation ratio by modeling a similarity computation time mathematically.

• 정보과학회 논문지
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• 제42권1호
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• pp.33-43
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• 2015

최근 특허영상의 중요도가 높아지면서 특허영상 검색에 대한 연구의 필요성이 커지고 있다. 그러나 지금까지 대부분의 특허검색은 이진 영상에서 에지 특징을 추출하는 방법을 주로 사용하고 있어서 영상 전처리 과정에서 에지 검출 결과에 따라 검색 성능이 영향을 받는 단점이 있다. 이러한 문제점을 해결하기 위해, 본 논문에서는 영상의 형태적 특징을 표현하는 SURF를 사용하여 특허영상의 특징을 표현하고 검색하는 방법을 제안한다. 제안하는 방법은 영상에서 SURF를 계산하여 관심점과 방향을 추출하고 영역별 히스토그램을 구한다. 제안하는 방법의 우수성을 평가하기 위해서 제안하는 방법을 2000 이진 특허 영상 데이터베이스에 적용하였고, 에지 정보가 일부 손실되더라도 검색 결과가 매우 뛰어남을 보여주었다.

• 한국컴퓨터정보학회논문지
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• 제5권3호
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• pp.215-219
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• 2000

The purpose of this paper is to propose a method to maximize the efficiency of a content-based image retrieval for various kinds of images. This paper discuss the self-adaptivity for the change of image domain and the self-selection of optimal features for query image, and present the efficient method to maximize content-based retrieval for various kinds of images. In this method, a content-based retrieval system is adopted to select automatically distinctive feature patterns which have a maximum efficiency of image retrieval in various kinds of images. Experimental results show that the Proposed method is improved 3% than the method using individual features.

• 컴퓨터교육학회논문지
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• 제8권1호
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• pp.81-91
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• 2005

본 논문에서는 칼라와 에지 정보를 이용한 내용기반 영상검색 기법을 제안하였다. 기존의 RGB 공간 정보를 이용하기 보다는, 시각적 인식에 보다 중점을 둔 HSI칼라 공간에서 고찰하였다. 비슷한 류의 색을 대표색으로 통합 표현하여, 개선된 칼라 정보 이용법을 본 연구에서 제안하였다. 또한 칼라 정보만을 이용했을 때의 시스템 성능상의 결점을 보완하기 위하여, 효율적인 에지 디텍션 기법을 함께 사용하였다. 칼라와 에지 기법을 통합함에 있어서, 각각의 기법에 적절한 가중치를 배분함으로써 시스템 성능을 실험적으로 향상시켰다.

• 대한임베디드공학회논문지
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• 제3권1호
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• pp.8-18
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• 2008

In this paper, we propose an efficient algorithm using wavelet transform for still image database retrieval. Especially, it uses only the lowest frequency sub-band in multi-level wavelet transform so that a retrieval system uses a smaller quantity of memory and takes a faster processing time. We extract different textured features, statistical information such as mean, variance and histogram, from low frequency sub-band. Then we measure the distances between the query image and the images in a database in terms of these features. To obtain good retrieval performance, we use the first feature (mean and variance of wavelet coefficients) to filter out most of the unlikely images. The rest of the images are considered to be candidate images. Then we apply the second feature (histogram of wavelet coefficient) to rank all the candidate images. To evaluate the algorithm, we create various distorted image databases using MIT VisTex texture images and PICS natural images. Through simulations, we demonstrate that our method can achieve performance satisfactorily in terms of the retrieval accuracy as well as the both memory requirement and computational complexity. Therefore it is expected to provide good retrieval solution for JPEG-2000 using wavelet transform.

• 한국멀티미디어학회논문지
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• 제6권2호
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• pp.240-246
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• 2003

본 논문에서는 웨이브릿 변환 영역에서 양방향 반올림 필터를 이용한 객체 영역 기반 고속 영상 검색 방법을 제안한다. 기존의 방법은 웨이브릿 변환 영역의 부대역 전체에서 특징 벡터를 추출하기 때문에 불필요한 배경 정보가 포함됨으로써 검색 효율이 감소하였다. 제안한 방법은 양방향 반올림 필터를 이용하여 객체 영역에서만 특징 벡터를 추출함으로써 불필요한 배경 정보를 제거하여 검색 효율을 향상시킨다. 그리고, 색상 정보에 관한 특징 벡터 수를 감소하여도 일정한 검색 효율을 유지한다. 결론적으로, 영상의 특성에 따라 다소 차이는 있으나 2.5%∼5.3%의 검색 효율이 향상됨을 알 수 있었다.

• Journal of Information Processing Systems
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• 제15권4호
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• pp.737-747
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• 2019

Shape description is an important and fundamental issue in content-based image retrieval (CBIR), and a number of shape description methods have been reported in the literature. For shape description, both global information and local contour variations play important roles. In this paper a new included-angular ternary pattern (IATP) based shape descriptor is proposed for shape image retrieval. For each point on the shape contour, IATP is derived from its neighbor points, and IATP has good properties for shape description. IATP is intrinsically invariant to rotation, translation and scaling. To enhance the description capability, multiscale IATP histogram is presented to describe both local and global information of shape. Then multiscale IATP histogram is combined with included-angular histogram for efficient shape retrieval. In the matching stage, cosine distance is used to measure shape features' similarity. Image retrieval experiments are conducted on the standard MPEG-7 shape database and Swedish leaf database. And the shape image retrieval performance of the proposed method is compared with other shape descriptors using the standard evaluation method. The experimental results of shape retrieval indicate that the proposed method reaches higher precision at the same recall value compared with other description method.