• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.10
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• pp.113-122
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• 1999

When we want to retrieve the most similar image from the image database, the color histogram intersection, shape feature and texture feature comparing method are used as a metric to measure the similarity. In order to increase the accuracy of retrievals, we need to integrate two different features. In this paper, the histogram intersection and shape based block histogram intersection method are used. This method results in a high efficient algorithm that meets a similar accuracy and a relatively fast retrieval speed compared to the method of integration of two different features. The Proposed algorithm is tested on retrievals of image database consisting of various 600 images and we implemented that the proposed algorithm gives fast, high efficiency and reliability compared to others.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.1
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• pp.10-16
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• 2007

In this paper, we propose a technique for retrieving images using spatial color correlation and texture characteristics based on local fourier transform. In order to retrieve images, two new descriptors are proposed. One is a color descriptor which represents spatial color correlation. The other is a descriptor combining the proposed color descriptor with texture descriptor. Since most of existing color descriptors including color correlogram which represent spatial color correlation considered just color distribution between neighborhood pixels, the structural information of neighborhood pixels is not considered. Therefore, a novel color descriptor which simultaneously represents spatial color distribution and structural information is proposed. The proposed color descriptor represents color distribution of Min-Max color pairs calculating color distance between center pixel and neighborhood pixels in a block with 3x3 size. Also, the structural information which indicates directional difference between minimum color and maximum color is simultaneously considered. Then new color descriptor(min-max color correlation descriptor, MMCCD) containing mean and variance values of each directional difference is generated. While the proposed color descriptor includes by far smaller feature vector over color correlogram, the proposed color descriptor improves 2.5 % ${\sim}$ 13.21% precision rate, compared with color correlogram. In addition, we propose a another descriptor which combines the proposed color descriptor and texture characteristics based on local fourier transform. The combined method reduces size of feature vector as well as shows improved results over existing methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.10C
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• pp.983-991
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• 2005

Human faces are commonly found in a video such as a drama and provide useful information for video content analysis. Therefore, face detection plays an important role in applications such as face recognition, and face image database management. In this paper, we propose a face detection algorithm based on pre-processing of scene change detection for indexing and cast searching in video. The proposed algorithm consists of three stages: scene change detection stage, face region detection stage, and eyes and mouth detection stage. Experimental results show that the proposed algorithm can detect faces successfully over a wide range of facial variations in scale, rotation, pose, and position, and the performance is improved by $24\%$with profile images comparing with conventional methods using color components.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.77-80
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• 2001

In general, the informations of the inner image that user interested in are limited to a special domain. In this paper, as using Wavelet Transform for dividing image into high frequency and low frequency, We can separate foreground including many data. After calculating object boundary of separated part, We extract special features using Color Coherence Vector. According to results of this experiment, the method of comparing data extracting foreground features is more effective than comparing data extracting features of entire image when we extract the image user interested in.

• Journal of Korean Library and Information Science Society
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• v.31 no.1
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• pp.229-258
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• 2000

The growth of digital image an video archives is increasing the need for tools that efficiently search through large amount of visual dta. Retrieval of visual data is important issue in multimedia database. We are using contented-based visual data retrieval method for efficient retrieval of visual data. In this paper, we introduced fundamental techniques using characteristic values of image data and indexing techniques required for content-based visual retrieval. In addition we introduced content-based visual retrieval system for use of digital library.

• Information and Communications Magazine
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• v.18 no.10
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• pp.75-87
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• 2001

방송 서비스는 이제 디지털 시대를 맞이하여 일대 패러다임의 변화를 겪고 있다. 전 세계는 본격적인 디지털 방송 시대를 맞이하고 있으며, 새로운 반송 환경에서는 기존의 서비스와는 비교할 수 없을 정도로 향상된 품질의 오디오비쥬얼 데이터를 제공할 뿐만 아니라, 시청자의 요구에 적절히 대응하는 대화형 멀티미디어 방송 서비스 제공이 가능해 진다. 이러한 방송 분야의 눈부신 발전에는 국제 표준화 기구인 ISO/IEC 산하의 동영상 전문가 그룹인 MPEG의 표준기술 개발이 큰 원동력이 되고 있다. 본 고에서는 대화형 방송의 개념과 기술을 중심으로 현재 진행되고 있는 방송 기술의 변화를 살펴보고, 객체 지반의 데이터 압축, 처리, 전송을 가능하게 하는 MPEG-4 및 내용 기반 검색 및 필터링을 가능하게 하는 MPEG-7 기술의 개념 및 방송 서비스 적용에 대해 검토해보기로 한다.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.453-456
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• 2003

Compared with other features of the image, color features are less sensitive to noise and background complication. Besides, this adding to object segmentation has more accuracy of image retrieval. This paper presents object segmentation and HAQ(Histogram Analysis and Quantization) algorithm approach to extract features(the object information and the characteristic colors) of an image. The empirical results shows that this method presents exactly spatial and color information of an image as image retrieval's feature.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.129-132
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• 2000

In this paper, we deal with content based searching algorithm for brand image using GHA(Generalized Hebbian Algorithm). GHA is a part of PCA(Principal Component Analysis), that has single-layer perceptron operates and self-organizing performances. We used this algorithm for feature extracts of brand images, and our simulations verify the high performance than present text based methods.

• The Transactions of the Korea Information Processing Society
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• v.5 no.9
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• pp.2294-2301
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• 1998

The aim of this paper is to extract features from each news scenes for example, symbol icon which can be distinct each broadcasting corp, icon and caption which are has feature and important information for the scene in respectively, In this paper, we propose extraction methods of caption that has important prohlem of news videos and it can be classified in three steps, First of al!, we converted that input images from video frame to YIQ color vector in first stage. And then, we divide input image into regions in clear hy using equalized color histogram of input image, In last, we extracts caption using edge histogram based on vertical and horizontal line, We also propose the method which can extract news icon in selected key frames by the difference of inter-histogram and can divide each scene by the extracted icon. In this paper, we used comparison method of edge histogram instead of complex methcxls based on color histogram or wavelet or moving objects, so we shorten computation through using simpler algorithm. and we shown good result of feature's extraction.

• Journal of Korea Multimedia Society
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• v.8 no.10
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• pp.1306-1313
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• 2005

Relevance Feedback(RF), a method to use perceptual feedback in image retrieval, refines a query by the relevance information from a user. However, the user's feedback information is thrown away as soon as a search session ends. So, this paper proposes an enhanced version of RF, which is designed to accumulate human perceptual responses over time through relevance feedback and to dynamically combine the accumulated high-level relevance information with low-level features to further improve the retrieval effectiveness. Experimental results are presented to prove the potential of the proposed RF.