• Title/Summary/Keyword: metric chroma

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New Weighting Functions for the Modified CIELAB Colour-Difference Formulae (수정 CIELAB 색차식을 위한 새로운 색차 가중 함수)

  • Kim, Dong-Ho
    • Textile Coloration and Finishing
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    • v.9 no.6
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    • pp.51-57
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    • 1997
  • The lightness, chroma and hue tolerances with respect to the standard colour position in the CIELAB space have been studied in detail using the various existing data sets and the set form this study. The lightness tolerance showed a clear dependency upon the metric lightness for medium to light colour, but in the case of dark colours there was a discrepancy between the data sets. Both the chroma and hue tolerances showed dependency upon both the chroma and hue-angle and not the single dependency upon the metric chroma, as assumed in the CIE94 formula. New weighting functions were derived from the above experimental evidence, and finally a new formula, LCD(Leeds Colour Difference) was proposed. The LCD formula is nearly as simple and flexible as CIE94 but smoothes the individual weighting functions, especially for lightness tolerances for light colours and chromaticity discrimination near the blue region.

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Design and Implementation of Matching Engine for QbSH System Based on Polyphonic Music (다성음원 기반 QbSH 시스템을 위한 매칭엔진의 설계 및 구현)

  • Park, Sung-Joo;Chung, Kwang-Sue
    • Journal of Korea Multimedia Society
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    • v.15 no.1
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    • pp.18-31
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    • 2012
  • This paper proposes a matching engine of query-by-singing/humming (QbSH) system which retrieves the most similar music information by comparing the input data with the extracted feature information from polyphonic music like MP3. The feature sequences transcribed from polyphonic music may have many errors. So, to reduce the influence of errors and improve the performance, the chroma-scale representation, compensation and asymmetric DTW (Dynamic Time Warping) are adopted in the matching engine. The performance of various distance metrics are also investigated in this paper. In our experiment, the proposed QbSH system achieves MRR (Mean Reciprocal Rank) of 0.718 for 1000 singing/humming queries when searching from a database of 450 polyphonic musics.