• The KIPS Transactions:PartB
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• v.9B no.6
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• pp.753-758
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• 2002

This paper proposes the color Cross-correlogram and its extraction method for efficient image retrieval. Color cross-correlogram represents the probability that different colors are existed at any two pixels whose distance is fixed in an image. Color cross-correlogram doesn't have the information about the region size that has a color, so color cross-correlogram can have good performance in retrieving images that have different size color regions. The experiments say that we can get the good retrieval results in the images that have various size color regions, and get the better retrieval results when using color cross-correlogram than those of retrieval using color correlogram.

• Journal of Korea Multimedia Society
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• v.4 no.6
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• pp.534-542
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• 2001

Recent content-based image retrieval systems make use of a local single server contained a limited number of images. So these systems are not satisfactory for the Web user's needs that make request for various images on the Web. A content-based image retrieval system that has regard for a great number of Web images has to stand on the basis of real-time first of all. Therefore, to implement the above system we have to resolve a problem of large waste time to take for an image collection and feature extractions. In recent, PC clusters with a load distribution are implemented for the purpose of high-performance data processing. In this paper, we decreased the whole retrieval time by distributing the tasks of image collection and feature extraction to take much time among the slave computers of the PC cluster, and so we found the possibility of the real-time processing in the retrieval of Web images.

• Journal of the Korea Society of Computer and Information
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• v.15 no.11
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• pp.75-82
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• 2010

The paper proposed CBIRS/EFI with contents based search technique using edge feature information of the object from image information of the object which is uncertain. In order to search specially efficiently case of partial image information of the object, we used the search technique which extracts outline information and color information in feature information of object. In order to experiment this, we extracted side edge feature information of the vehicle for feature information of the object after capture the car image of the underground garage. This is the system which applies a contents base search by the result which analyzes the image which extracts a feature, an original image to search and a last similar measurement result. This system compared in FE-CBIRS systems which are an existing feature extraction contents base image retrieval system and the function which improves the accuracy and an effectiveness of search rate was complemented. The performance appraisal of CBIRS/EFI systems applied edge extraction feature information and color information of the cars. And we compared a color feature search time, a shape characteristic search time and a search rate from the process which searches area feature information. We extracted the case 91.84% of car edge feature extraction rate. And a average search time of CBIRS/EFI is showing a difference of average 0.4-0.9 seconds than FE-CBIRS from vehicle. color search time, shape characteristic search time and similar search time. So, it was proven with the fact that is excellent.

• The Journal of Information Technology and Database
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• v.6 no.2
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• pp.19-28
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• 1999

Digital image and video libraries require new algorithms for the automated extraction and indexing of salient image features. Eigen values of an image provide one important cue for the discrimination of image content. In this paper we propose a new approach for automated content extraction that allows efficient database searching using eigen values. The algorithm automatically extracts eigen values from the image matrix represented by the covariance matrix for the image. We demonstrate that the eigen values representing shape information and the skewness of its distribution representing complexity provide good performance in image query response time while providing effective discriminability. We present the eigen value extraction and indexing techniques. We test the proposed algorithm of searching by eigen value and its skewness on a database of 100 images.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1855-1858
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• 2003

In this paper, we propose image retrieval method more accurate and efficient than the conventional one. First of ail, we perform a shot 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[I][2]. We get principal axis applying PCA(Principal Component Analysis) to key frames for obtaining indexing information, and divide a domain. Video retrieval uses indexing information of high dimension. We apply KD-Trees(K Dimensional-Trees)[3] which shows efficient retrieval in data set of high dimension to video retrieval method. The proposed method can represent property of images more efficiently and property of domains more accurately using KD-Trees.

• The Transactions of the Korea Information Processing Society
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• v.3 no.4
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• pp.733-744
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• 1996

Content-based image retrieval(CBIR) is an image data retrieval methodology using characteristic values of image data those are generated by system automatically without any caption or text information. In this paper, we propose a content-based image data retrieval method using shape and color features of image data as characteristic values. For this, we present some image processing techniques used for feature extraction and indexing techniques based on trie and R tree for fast image data retrieval. In our approach, image query result is more reliable because both shape and color features are considered. Also, we how an image database which implemented according to our approaches and sample retrieval results which are selected by our system from 200 sample images, and an analysis about the result by considering the effect of characteristic values of shape and color.

• Journal of Korean Library and Information Science Society
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• v.35 no.3
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• pp.271-291
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• 2004

Such information services source like digital library has been asked information services of atypical multimedia database like image, voice, VOD/AOD. Examined in this study are suggestions such as word-phrase generator, syllable recoverer, morphological analyzer, corrector for voice processing. Suggested voice processing technique transform voice database into tort database, then extract index database from text database. On top of this, the study suggest a information retrieval model to use in extracted index database, voice full-text information retrieval.

• Journal of the HCI Society of Korea
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• v.1 no.2
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• pp.27-33
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• 2006

This paper presents a new approach to translation and rotation invariant feature extraction for image texture retrieval. For the rotation invariant feature extraction, we invent angular projection along angular frequency in Polar coordinate system. The translation and rotation invariant feature vector for representing texture images is constructed by the averaged magnitude and the standard deviations of the magnitude of the Fourier transform spectrum obtained by the proposed angular projection. In order to easily implement the angular projection, the Radon transform is employed to obtain the Fourier transform spectrum of images in the Polar coordinate system. Then, angular projection is applied to extract the feature vector. We present our experimental results to show the robustness against the image rotation and the discriminatory capability for different texture images using MPEG-7 data set. Our Experiment result shows that the proposed rotation and translation invariant feature vector is effective in retrieval performance for the texture images with homogeneity, isotropy and local directionality.

• Journal of the Semiconductor & Display Technology
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• v.12 no.3
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• pp.59-64
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• 2013

Accurate and robust image registration is important task in many applications such as image retrieval and computer vision. To perform the image registration, essential required steps are needed in the process: feature detection, extraction, matching, and reconstruction of image. In the process of these function, feature extraction not only plays a key role, but also have a big effect on its performance. There are two representative algorithms for extracting image features, which are scale invariant feature transform (SIFT) and speeded up robust feature (SURF). In this paper, we present and evaluate two methods, focusing on comparative analysis of the performance. Experiments for accurate and robust feature detection are shown on various environments such like scale changes, rotation and affine transformation. Experimental trials revealed that SURF algorithm exhibited a significant result in both extracting feature points and matching time, compared to SIFT method.

• Journal of KIISE:Software and Applications
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• v.32 no.9
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• pp.853-867
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• 2005

A number of content-based image search methods have been proposed to this point. Each of these systems uses different image data and generates different data depending on the extraction method of different characteristics that the search capabilities of each system cannot be compared and assessed. In particular, there is a problem of applying the identical image data onto the contents based image search system on the web that cannot be compared and assessed. To resolve such a problem, the XML-based FEMAL is hereby presented for extracting data of characteristics generated from specific search system in a way that can be recognized from other starch system. In the experiment using FEMAL, the extract data for characteristics is mutually communicated and integrated and the comparison assessment of search capability is seemed to be available.