面粉麸星的计算机检测
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摘要
传统的面粉麸星检测都是靠人工感官方式,由于麸星的数量多而面积小,靠人工感官检测方式只能对麸星的多少进行定性分析难以给出具体数量。本文着重介绍以计算机模式识别方式精确计算面粉单位面积的麸星个数、单个麸星的面积大小、麸星的总面积、麸星的总面积占面粉单位面积的百分比等量化值。
The traditional test of bran specks in wheat flour is entirely subjective. Since the bran specks are small and numerous, the traditional test can only give a qualitative analysis instead of a quantitative one. In this paper, a computer pattern recognition based method is proposed to accurately calculate the individual area of a bran speck, and the bran speck number per unit flour area. Consequently, the total area of bran specks can be derived, together with the percentage of bran speck area in unit flour area.
The traditional test of bran specks in wheat flour is entirely subjective. Since the bran specks are small and numerous, the traditional test can only give a qualitative analysis instead of a quantitative one. In this paper, a computer pattern recognition based method is proposed to accurately calculate the individual area of a bran speck, and the bran speck number per unit flour area. Consequently, the total area of bran specks can be derived, together with the percentage of bran speck area in unit flour area.
引文
〔1〕 刘兴信.关于我国小麦粉质量标准问题的探讨中国粮油学报,2002,5(1):1-6
〔2〕 范璐,周展明,汤坚.图象分析测定红麦硬度方法的研究中国粮油学报,2002,6(7):28-30
〔3〕 傅德成,孙英.食品质量感官鉴别指南中国标准出版社,1994,2
〔4〕 粮食食品检验编写组粮食食品检验中国财经出版社,1992,4
〔5〕 GB1355-1986小麦粉国家标准
〔6〕 边肇祺,张学工等编著.模式识别(第二版).北京:清华大学出版社,2000
〔7〕 王碧泉,陈祖荫.模式识别理论、方法和应用.北京:地震出版社,1989
〔8〕 王守觉.仿生模式识别(拓扑模式识别)———一种模式识别新模型的理论与应用.电子学报,2002,30(10):1417-1420
〔9〕 JainAK,DuinRPW,JianchangMaoStatisticalpatternrecognition: areviewPatternAnalysisandMachineIntelli gence,IEEETransactionson,2000,22(1):4-37
〔10〕 WangJunsheng,LiMinqiang.Amulti-factorialdecision-makingmodelfordeductionofrulesinroughsetsIntel ligentControlandAutomation,2000.Proceedingsofthe3rdWorldCongresson,2000,(1):383-386
〔11〕 YingZhu,SchwartzS.Discriminantanalysisandadaptivewaveletfeatureselectionforstatisticalobjectdetection.PatternRecognition,2002.Proceedings.16thInternationalConferenceon,2002,(4):86-89
〔12〕 RuedaLG,OommenBJ.Onoptimalpairwiselinearclassifiersfornormaldistributions: thetwo-dimensionalcase.PatternAnalysisandMachineIntelligence,IEEETransactionson,2002,24(2):274-280
〔13〕 wamuraM,OmachiS,AsoH.Amodificationofeigen valuestocompensateestimationerrorsofeigenvectorsPatternRecognition,2000Proceedings.15thInterna tionalConferenceon,2000,(2):378-381
〔14〕 孙即祥.现代模式识别.国防大学出版社,20015
〔2〕 范璐,周展明,汤坚.图象分析测定红麦硬度方法的研究中国粮油学报,2002,6(7):28-30
〔3〕 傅德成,孙英.食品质量感官鉴别指南中国标准出版社,1994,2
〔4〕 粮食食品检验编写组粮食食品检验中国财经出版社,1992,4
〔5〕 GB1355-1986小麦粉国家标准
〔6〕 边肇祺,张学工等编著.模式识别(第二版).北京:清华大学出版社,2000
〔7〕 王碧泉,陈祖荫.模式识别理论、方法和应用.北京:地震出版社,1989
〔8〕 王守觉.仿生模式识别(拓扑模式识别)———一种模式识别新模型的理论与应用.电子学报,2002,30(10):1417-1420
〔9〕 JainAK,DuinRPW,JianchangMaoStatisticalpatternrecognition: areviewPatternAnalysisandMachineIntelli gence,IEEETransactionson,2000,22(1):4-37
〔10〕 WangJunsheng,LiMinqiang.Amulti-factorialdecision-makingmodelfordeductionofrulesinroughsetsIntel ligentControlandAutomation,2000.Proceedingsofthe3rdWorldCongresson,2000,(1):383-386
〔11〕 YingZhu,SchwartzS.Discriminantanalysisandadaptivewaveletfeatureselectionforstatisticalobjectdetection.PatternRecognition,2002.Proceedings.16thInternationalConferenceon,2002,(4):86-89
〔12〕 RuedaLG,OommenBJ.Onoptimalpairwiselinearclassifiersfornormaldistributions: thetwo-dimensionalcase.PatternAnalysisandMachineIntelligence,IEEETransactionson,2002,24(2):274-280
〔13〕 wamuraM,OmachiS,AsoH.Amodificationofeigen valuestocompensateestimationerrorsofeigenvectorsPatternRecognition,2000Proceedings.15thInterna tionalConferenceon,2000,(2):378-381
〔14〕 孙即祥.现代模式识别.国防大学出版社,20015
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