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      부유선별공정 모니터링을 위한 다변수 가우시안 혼합모델기반 색상 분석 = Color Analysis Based on Multivariate Gaussian Mixture Models for Froth Flotation Monitoring

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      https://www.riss.kr/link?id=A108551670

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      다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

      Froth flotation is a type of mineral processing that selectively separates useful minerals from the froth produced by pulp aeration. The physical features of the froth contain information to understand the status of the process of froth flotation. In particular, by obtaining the color feature of the froth, it is possible to predict not only the type of useful mineral but also the grade of the mineral. Therefore, it is very important to obtain high-precision color analysis results in froth flotation monitoring. In this paper, we propose a color analysis method based on multivariate Gaussian mixture models to guarantee the cyclicity with a period of 360 degrees in hue component of color. In order to verify the proposed method, we present the color analysis results of images which contain around () of hue and images obtained by froth flotation. Through the experimental results, it shows that the color analysis results obtained by the proposed method are more precise.
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      Froth flotation is a type of mineral processing that selectively separates useful minerals from the froth produced by pulp aeration. The physical features of the froth contain information to understand the status of the process of froth flotation. In ...

      Froth flotation is a type of mineral processing that selectively separates useful minerals from the froth produced by pulp aeration. The physical features of the froth contain information to understand the status of the process of froth flotation. In particular, by obtaining the color feature of the froth, it is possible to predict not only the type of useful mineral but also the grade of the mineral. Therefore, it is very important to obtain high-precision color analysis results in froth flotation monitoring. In this paper, we propose a color analysis method based on multivariate Gaussian mixture models to guarantee the cyclicity with a period of 360 degrees in hue component of color. In order to verify the proposed method, we present the color analysis results of images which contain around () of hue and images obtained by froth flotation. Through the experimental results, it shows that the color analysis results obtained by the proposed method are more precise.

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      참고문헌 (Reference)

      1 박순영 ; 조완현 ; 이명은, "모폴로지 연산과 가우시안 혼합 모형에 기반한 컬러 영상 분할" 대한전자공학회 43 (43): 84-91, 2006

      2 전미진 ; 이준재, "가우시안 혼합 모델 기반의 영상 히스토그램 평활화" 한국멀티미디어학회 15 (15): 748-760, 2012

      3 S.H. Morar, "The Use of A Colour Parameter in A Machine Vision System, Smart-Froth, to Evaluate Copper Flotation Performance at Rio Tinto’s Kennecott Utah Copper Concentrator" 147-151, 2005

      4 J.M. Oestreich, "The Development of a Color Sensor System to Measure Mineral Compositions" 8 (8): 31-39, 1995

      5 "Stunning colorful flower bed"

      6 D. Zhang, "Soft Sensor of Iron Tailings Grade Based on Froth Image Feature for Reverse Flotation" 44 (44): 2928-2940, 2022

      7 O. Haavisto, "Optical Spectrum Based Measurement of Flotation Slurry Contents" 88 (88): 80-88, 2008

      8 C. Aldrich, "Online Monitoring and Control of Froth Flotation Systems with Machine Vision:A Review" 96 (96): 1-13, 2010

      9 M. Kistner, "Monitoring of Mineral Processing Systems by Using Textural Image Analysis" 52 : 169-177, 2013

      10 안재원 ; 고윤호, "HLS 색상 공간에서 동영상의 안개제거 기법" 한국멀티미디어학회 20 (20): 32-42, 2017

      1 박순영 ; 조완현 ; 이명은, "모폴로지 연산과 가우시안 혼합 모형에 기반한 컬러 영상 분할" 대한전자공학회 43 (43): 84-91, 2006

      2 전미진 ; 이준재, "가우시안 혼합 모델 기반의 영상 히스토그램 평활화" 한국멀티미디어학회 15 (15): 748-760, 2012

      3 S.H. Morar, "The Use of A Colour Parameter in A Machine Vision System, Smart-Froth, to Evaluate Copper Flotation Performance at Rio Tinto’s Kennecott Utah Copper Concentrator" 147-151, 2005

      4 J.M. Oestreich, "The Development of a Color Sensor System to Measure Mineral Compositions" 8 (8): 31-39, 1995

      5 "Stunning colorful flower bed"

      6 D. Zhang, "Soft Sensor of Iron Tailings Grade Based on Froth Image Feature for Reverse Flotation" 44 (44): 2928-2940, 2022

      7 O. Haavisto, "Optical Spectrum Based Measurement of Flotation Slurry Contents" 88 (88): 80-88, 2008

      8 C. Aldrich, "Online Monitoring and Control of Froth Flotation Systems with Machine Vision:A Review" 96 (96): 1-13, 2010

      9 M. Kistner, "Monitoring of Mineral Processing Systems by Using Textural Image Analysis" 52 : 169-177, 2013

      10 안재원 ; 고윤호, "HLS 색상 공간에서 동영상의 안개제거 기법" 한국멀티미디어학회 20 (20): 32-42, 2017

      11 J.M. Hargrave, "Diagnosis of Concentrate Grade and Mass Flowrate in Tin Flotation from Colour and Surface Texture Analysis" 10 (10): 613-621, 1997

      12 G. Bonifazi, "Characterisation of Flotation Froth Colour and Structure by Machine Vision" 27 (27): 1111-1117, 2001

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