• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.240-243
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• 2000

An apparel products retrieval system was proposed in which users can refer to products using Kansei evaluation values. The system adopts relevance feedback using history of the retrieval to learn the tendency of user evaluation. The system is based on a vector space retrieval model using products images expression as semantic scales. The system makes a query from user inputting information and retrieves closest products from the database. Revising algorithms of the difference method. linear multiple regression performed to investigate the effectiveness and criteria of the search. As a result of evaluation of the accuracy, it was found that the linear multiple regression and the neural network models are effective for the retrieval considering the individual Kansei.

• Journal of Korea Multimedia Society
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• v.6 no.6
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• pp.1008-1014
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• 2003

In this paper, we propose the image retrieval method based on object regions using bidirectional round filter in the wavelet transform domain. A conventional method that includes unnecessary background information reduce retrieval efficiency, because of the extraction of feature vectors from the whole region of subband. On proposed method, it extracts accurate feature vectors and keep certainly retrieval efficiency in case of reduced feature vectors, because of the extraction of feature vectors from the only extracted object region. Furthermore, it improve retrieval efficiency by removing unnecessary background information. Consequently, the retrieval efficiency is improved with 2.5%∼5.5% values, which have a little chances to vary according to characteristics of image.

• Journal of Information Processing Systems
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• v.13 no.3
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• pp.464-475
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• 2017

In this paper, we present a new texture image retrieval method which combines color and texture features extracted from images by a set of multi-resolution multi-direction (MRMD) filters. The MRMD filter set chosen is simple and can be separable to low and high frequency information, and provides efficient multi-resolution and multi-direction analysis. The color space used is HSV color space separable to hue, saturation, and value components, which are easily analyzed as showing characteristics similar to the human visual system. This experiment is conducted by comparing precision vs. recall of retrieval and feature vector dimensions. Images for experiments include Corel DB and VisTex DB; Corel_MR DB and VisTex_MR DB, which are transformed from the aforementioned two DBs to have multi-resolution images; and Corel_MD DB and VisTex_MD DB, transformed from the two DBs to have multi-direction images. According to the experimental results, the proposed method improves upon the existing methods in aspects of precision and recall of retrieval, and also reduces feature vector dimensions.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.5
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• pp.43-51
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• 2009

In this paper, we propose an efficient method of face retrieval by using PCA(principal component analysis) based features. The coarse-to-fine strategy is adopted to sort the retrieval results in the lower dimensional eigenface space and to rearrange candidates at high ranks in higher dimensional eigenface space. To evaluate similarity between a query face image and class reference image, we utilize the PD (projection distance), MQDF(modified quadratic distance function) and MED(minimum Euclidean distance). The experimental results show that the proposed method which rearrange the retrieval results incrementally by using projection distance is efficient for face image retrieval.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.8
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• pp.1782-1789
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• 1997

Most systems that retrieve distributed information on the Internet have difficulties in retrieving relevant information for they are not able to reflect exact semantics on retrieval queries that usersrequest. In this paepr, we propose an automatic query expansion based on ter distribution which reflects semantics of retrieval term to emhance the performance of information retrieval. We computed weight, indicating its overal imoritance in the collection documents and user's query and we use LSI's SVD technique to measure the term distribution which appears similar to query. And also, we measure the similarity to compared numerical value with query terms. Also we researched the method to reduce additional terms automatically and evaluated the performance of the proposed method.

• Archives of design research
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• v.20 no.3 s.71
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• pp.203-214
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• 2007

This study proposes an information retrieval method reflecting the user's preferences based on the fuzzy set theory to develop information contents which support pedestrian's navigation. Firstly, the research evaluated subjects' preferences on commercial spaces set to a hypothetical destination. Also it surveyed the causal relationship between the visual characteristics and the emotional characteristics to propose methods of Navigation Knowledge Base (NKB). The NKB was composed of three elements; 1. the correlation model between emotional characteristics, 2. the causal relationship between visual characteristics and emotional characteristics, 3. the transformation model between visual characteristics and the physical characteristics. Secondly, this study classified the pedestrian's destination search into 4 types with his or her preferences and the time conditions limited during navigation. For each type it presented the Destination Search Algorithm (DSA). Finally, the research simulated the destination search in 4 navigation types using NKB and DSA and verified the availability of the information retrieval method reflecting pedestrian's preferences. In conclusion, the proposed information search method will be applied to reflect the user's preferences to develop information appliances.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1676-1689
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• 2014

At present, the Content-Based Image Retrieval (CBIR) system has become a hot research topic in the computer vision field. In the CBIR system, the accurate extractions of low-level features can reduce the gaps between high-level semantics and improve retrieval precision. This paper puts forward a new retrieval method aiming at the problems of high computational complexities and low precision of global feature extraction algorithms. The establishment of the new retrieval method is on the basis of the SIFT and Harris (APISH) algorithm, and the salient region of interest points (SRIP) algorithm to satisfy users' interests in the specific targets of images. In the first place, by using the IPDSH and SRIP algorithms, we tested stable interest points and found salient regions. The interest points in the salient region were named as salient interest points. Secondary, we extracted the pseudo-Zernike moments of the salient interest points' neighborhood as the feature vectors. Finally, we calculated the similarities between query and database images. Finally, We conducted this experiment based on the Caltech-101 database. By studying the experiment, the results have shown that this new retrieval method can decrease the interference of unstable interest points in the regions of non-interests and improve the ratios of accuracy and recall.

• The Journal of the Acoustical Society of Korea
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• v.28 no.7
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• pp.674-679
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• 2009

This paper proposes a method of player event retrieval using combination of two functions: detection of player name in speech information and detection of sound event from audio information in golf videos. The system consists of indexing module and retrieval module. At the indexing time audio segmentation and noise reduction are applied to audio stream demultiplexed from the golf videos. The noise-reduced speech is then fed into speech recognizer, which outputs spoken descriptors. The player name and sound event are indexed by the spoken descriptors. At search time, text query is converted into phoneme sequences. The lists of each query term are retrieved through a description matcher to identify full and partial phrase hits. For the retrieval of the player name, this paper compares the results of word-based, phoneme-based, and hybrid approach.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2S
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• pp.692-700
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• 2000

As the multimedia application services have been getting various in Internet, need of multimedia database management system which can manage various multimedia information effectively has been increased. The multimedia application generally needs the features to store, manage, retrieve the multimedia data. We need a database management system framework that may be easily integrated with these features. This paper proposes th database management system framework providing the easy integration with various multimedia information retrieval. The framework uses OQL as the retrieval interface, so that user can use it easily. It can be integrated dynamically and easily with various multimedia retrieval method as a loosely coupled system. In addition there is no performance degradation caused in a loosely coupled system.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.508-510
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• 2002

인터넷의 발전과 더불어 기하급수적으로 늘어난 디지털 정보를 대상으로 사용자의 요구를 만족시키는 정보검색을 하기 위해 자연어처리 기술이 많이 응용되고 있다. 본 논문에서는 정보검색에 자연어 처리 기술 중, 의미중의성 해소(WSD) 기술을 적용하였다. HANTEC 12만 문서를 대상으로 9개의 중의성 단어를 실험한 결과 67.8%의 정확률을 보였다. 본 실험을 통해 WSD의 오분석이 정보검색의 정확률에 상당히 민감한 결과를 초래함을 알 수 있었다. 그리고, WSD 기술이 정보검색에 적용된 떼 발생할 수 있는 여러 문제점들에 대하여 논의하였고, 이 문제점의 근원적인 해결방안은 WSD기술의 발전에 있다는 것을 알 수 있었다.