title: [Identification of special quality eggs with NIR spectroscopy technology based on symbol entropy feature extraction method].
abstract: Fast, nondestructive and accurate identification of special quality eggs is an urgent problem. The present paper proposed a new feature extraction method based on symbol entropy to identify near infrared spectroscopy of special quality eggs. The authors selected normal eggs, free range eggs, selenium-enriched eggs and zinc-enriched eggs as research objects and measured the near-infrared diffuse reflectance spectra in the range of 12 000-4 000 cm(-1). Raw spectra were symbolically represented with aggregation approximation algorithm and symbolic entropy was extracted as feature vector. An error-correcting output codes multiclass support vector machine classifier was designed to identify the spectrum. Symbolic entropy feature is robust when parameter changed and the highest recognition rate reaches up to 100%. The results show that the identification method of special quality eggs using near-infrared is feasible and the symbol entropy can be used as a new feature extraction method of near-infrared spectra.
authors.affiliation: Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China. zhaoyong@ysu.edu.cn
authors.forename: Yong
authors.initials: Y
authors.lastname: Zhao
authors.forename: Wen-Xue
authors.initials: WX
authors.lastname: Hong
mesh_terms: D000465:Algorithms; D004531:Eggs / Q000032:analysis*; D019277:Entropy; D063427:Food Quality; D011786:Quality Control; D019265:Spectroscopy, Near-Infrared; D060388:Support Vector Machine