• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.585-589
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• 2002

In this paper, hierarchical retrieval system based on efficient feature extraction is proposed. In order to retrieval the image with robustness for geometrical transformation such as translation, scaling, and rotation. After performing the 2-level wavelet transform on image, We extract moment in low-level subband which was subdivided into subimages and texture feature, contrast of GLCM(Gray Level Co-occurrence Matrix). At first we retrieve the candidate images in database by the ones of image. To perform a more accurate image retrieval, the edge information on the high-level subband was subdivided horizontally, vertically and diagonally. And then, the energy rate of edge per direction was determined and used to compare the energy rate of edge between images for higher accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.8C
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• pp.783-792
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• 2005

This paper proposes a feature extraction method for sketch-based image retrieval of animation character. We extract the specific regions using the detection of scene change and correlation points between two frames, and the property of animation production. We detect the area of focused similar colors in extracted specific region. And it is used as feature descriptor for image retrieval that focused color(FC) of regions, size, relation between FCs. Finally, an user can retrieve the similar character using property of animation production and user's sketch as a query Image.

• Journal of KIISE:Databases
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• v.30 no.2
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• pp.125-133
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• 2003

In this paper we propose an efficient content-based image retrieval method using the color and wavelet based texture features. The color features are obtained from soft-color histograms of the global image and the wavelet-based texture features are obtained from the invariant moments of the high-pass sub-band through the spatial-frequency analysis of the wavelet transform. The proposed system, called a color and texture based two-step retrieval(CTBTR), is composed of two-step query operations for an efficient image retrieval. In the first-step matching operation, the color histogram features are used to filter out the dissimilar images quickly from a large image database. The second-step matching operation applies the wavelet based texture features to the retained set of images to retrieve all relevant images successfully. The experimental results show that the proposed algorithm yields more improved retrieval accuracy with computationally efficiency than the previous methods.

• The Transactions of the Korea Information Processing Society
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• v.5 no.8
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• pp.1951-1959
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• 1998

In this paper, we propose an efficient feature extaetion method for content-based approach and implement an image retrieval system in the Oracle database. First, we estract color feature by the modified Stricker's method from input images, and this color feature and ART2 neural network are used for the rough classification of images. Next, we extract texture feature using wavelet transform, and finally exeute the detailed classification on the rough classified images from the previous step. Exsing the proposed feature extraction methods, we implement a useful image retrieval system by Extended SQI, statement on the relational database. The proposed system is implemented on the Oracle DBMS, and in the experimental results with 200 sample images, it shows the retrieval rate 90% and 81% in Recall and Precision, respectively.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.4
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• pp.113-120
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• 2004

In this paper, we propose an efficient feature extraction and image retrieval algorithm for content-based retrieval method. First, we extract the object using Gaussian edge detector for input image which is key frames of MPEG video and extract the object features that are location feature, distributed dimension feature and invariant moments feature. Next, we extract the characteristic color feature using the proposed HAQ(Histogram Analysis md Quantization) algorithm. Finally, we implement an retrieval of four features in sequence with the proposed matching method for query image which is a shot frame except the key frames of MPEG video. The purpose of this paper is to propose the novel content-based image retrieval algerian which retrieves the key frame in the shot boundary of MPEG video belonging to the scene requested by user. The experimental results show an efficient retrieval for 836 sample images in 10 music videos using the proposed algorithm.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.21-23
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• 2006

Due to development of Internet network environments and data compression techniques, the size and amount of multimedia data has greatly increased. They are compressed before transmission or storage. Dealing with these compressed data such as video retrieval or indexing requires the decoding procedure most of the time. In video retrieval and indexing a color histogram is one of the most frequently used tools. We propose a novel scheme for extracting color histograms from images transformed into the compressed domain using $8{times}8$ DCT(Discrete Cosine Transform). In this scheme an averaged version of original image is obtained by filtering DCT coefficients with a filter we destined.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.1
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• pp.28-33
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• 2003

This paper proposes a database index and retrieval method using the PCA(Principal Component Analysis). We perform a scene change detection and key frame extraction from the DC Image constructed by DCT DC coefficients in the compressed video stream that is video compression standard such as MPEG. In the extracted key frame, we use the PCA, then we can make codebook that has a statistical data as a codeword, which is saved as a database index. We also provide retrieval image that are similar to user's query image in a video database. As a result of experiments, we confirmed that the proposed method clearly showed superior performance in video retrieval and reduced computation time and memory space.

• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.133-139
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• 2006

Multimedia data is increasing rapidly by development of computer Information technology. Specially, quick and accurate processing of image data is required in image retrieval field. But it is difficult to guarantee both quickness and accuracy. This article suggests the algorithm that extracts representative features of image using genetic algorithm to solve this problem. This algorithm guarantees quickness and accuracy of retrieval by extracting representative features of image. We used color and texture as feature of image. Experiment shows that feature extracting method that is proposed is more accurate than existing study. So this study establishes propriety of method that is proposed.

• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.705-710
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• 2003

Recent years, as a rapid development of multimedia technology, video database system to retrieve video data efficiently seems to core technology in the oriented society. This thesis describes an efficient automatic frame detection and location method for content based retrieval of video. Frame extraction part is consist of incoming / outgoing car frame extraction and car number frame extraction stage. We gain star/end time of car video also car number frames. Frames are selected at fixed time interval from video and key frames are selected by color scale histogram and edge operation method. Car frame recognized can be searched by content based retrieval method.

• Journal of Korea Game Society
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• v.11 no.2
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• pp.115-129
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• 2011

In this paper, we will introduce some method about retrieving suitable images to game or adjusting game difficulty in enjoying some contents like mini-game. It will use the technology about extracting color and texture features in content-based image retrieval in image processing. So in card game, it select card image automatically. And by controlling seed image number, we can adjusting game difficulty. Through the experiment, it shows that our image retrieval method can retrieve more useful images that can be used in game than others.