• The Journal of the Acoustical Society of Korea
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• v.28 no.4
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• pp.375-382
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• 2009

This paper proposes a new audio fingerprinting method based on compressed-domain features. By basing on the compressed domain, the computational efficiency of the proposed method can be greatly enhanced. Especially we deal with MDCT domain, which is widely employed in audio compression, and extract three kinds of subband features; energy, centroid, and flatness. By taking signs after differentially filtering each feature, binary audio fingerprints are obtained. The identification performance of the three kinds of fingerprints are experimentally compared. Among the considered compressed-domain subband features, the subband energy showed the best performance for fingerprinting.

• Journal of KIISE:Databases
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• v.41 no.4
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• pp.199-208
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• 2014

In this paper, we represent a system of identification and feature search for scanned comics in consideration of their content characteristics. For creating the feature of the scanned comics, we utilize a method of hierarchical symmetry fingerprinting. Proposed identification and search system is designed to give online service provider, such as Webhard, an immediate identification result under conditions of huge volume of the scanned comics. In simulation part, we analyze the robustness of the identification of the fingerprint to image modification such as rotation and translation. Also, we represent a structure of database for fast matching in feature point database, and compare search performance between other existing searching methods such as full-search and most significant feature search.

• ETRI Journal
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• v.32 no.3
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• pp.490-492
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• 2010

This letter proposes a robust feature extraction method using a spatially normalized mean for temporal ordinal measurement. Before computing a rank matrix from the mean values of non-overlapped blocks, each block mean is normalized so that it obeys the invariance property against linear additive and subtractive noise effects and is insensitive against multiplied and divided noise effects. Then, the temporal ordinal measures of spatially normalized mean values are computed for the feature matching. The performance of the proposed method showed about 95% accuracy in both precision and recall rates on various distortion environments, which represents the 2.7% higher performance on average compared to the temporal ordinal measurement.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.2
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• pp.95-106
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• 2007

This paper proposes an effective tempo feature extraction method for music information retrieval. The tempo information is modeled by the narrow-band temporal modulation components, which are decomposed into a modulation spectrum via joint frequency analysis. In implementation, the tempo feature is directly extracted from the modified discrete cosine transform coefficients, which is the output of partial MP3(MPEG 1 Layer 3) decoder. Then, different features are extracted from the amplitudes of modulation spectrum and applied to different music information retrieval tasks. The logarithmic scale modulation frequency coefficients are employed in automatic music emotion classification and music genre classification. The classification precision in both systems is improved significantly. The bit vectors derived from adaptive modulation spectrum is used in audio fingerprinting task That is proved to be able to achieve high robustness in this application. The experimental results in these tasks validate the effectiveness of the proposed tempo feature.

• The Journal of the Korea Contents Association
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• v.12 no.5
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• pp.1-9
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• 2012

The popularity of digital music and smart phones led to develope noise-robust real-time audio fingerprinting system in various ways. In particular, The Multiple Hashing(MLH) of fingerprint algorithms is robust to noise and has an elaborate structure. In this paper, we propose a filter engine based on MLH to achieve better performance. In this approach, we compose a energy-intensive filter to improve the accuracy of Q/R from music database and a statistic filter to remove continuity and redundancy. The energy-intensive filter uses the Discrite Cosine Transform(DCT)'s feature gathering energy to low-order bits and the statistic filters use the correlation between searched fingerprint's information. Experimental results show that the superiority of proposed algorithm consists of the energy and statistical filtering in noise environment. It is found that the proposed filter engine achieves more robust to noise than Philips Robust Hash(PRH), and a more compact way than MLH.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.411-413
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• 2010

The wireless AP positioning system is under active progress regarding research and commercialization due to its merit of being able to overcome the representing demerits of existing GPS positioning, which are signal distortion and poor signal reception. This system's feature is to collect AP information distributed throughout the real world, store it on database, and execute positioning by comparing with searched AP information. The positioning process uses collected data, whereas comparison of database data uses the fingerprinting method. The fingerprinting method is a probabilistic modeling method that acquires as much of the data collected from one location upon database composition, to store the value's average value and use it in positioning. Yet, using the average value may contain the probability of errors. Such errors are fatal weaknesses for services based on the background of accurate positioning. This paper deals with the characteristics and problems of the previously used wireless AP positioning system, and proposes measures of using AP information for outdoor positioning in order to solve the aforementioned problems.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.131-137
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• 2014

Although illegal reproduction of cartoon books are prevalent with rapid growth of webhard services and smartphone use, fingerprinting technology for product identification, as seen in music and videos, has not been developed yet. This leads to indiscriminate illegal reproduction of cartoon books, causing great amount of copyright damages from copyright infringement of the rightful owners. The copyright R&D project granted from the Korea Copyright Permission (Project Title: Identification and Copy Protection Technology of Bookscaned Text/Comic Books) has been carried out in order to develop technology to effectively identify illegal reproduction and distribution of scanned cartoon books. The developed technology will contribute to increase of royalty payments and robust ecosystem of cartoon book markets. The study is to propose an enhanced implementation model for identification of scanned cartoon books on the basis of hierarchical symmetric difference feature algorithms adopted from existing feature extraction algorithms for video.