Application of full spectral matching algorithm in apple classification

• Published in: Nong ye gong cheng xue bao Vol. 29; no. 19; pp. 285 - 292
• Main Authors: Zhou, Wanhuai, Xie, Lijuan, Ying, Yibin
• Format: Journal Article
• Language: Chinese
• Published: 01.10.2013
• Subjects: Accuracy; Algorithms; Data base management systems; Matching; Raw; Similarity; Spectra
• ISSN: 1002-6819
• DOI: 10.3969/j.issn.1002-6819.2013.19.035

A spectral database system (SDBS) can improve the usage efficiency and expand the application scope of spectra and their feature information, mainly referring to spectral peak information. The spectral matching algorithm (SMA) plays a decisive role in SDBS for the SMA which determines the similarity between the sample spectrum and reference spectrum, and further, decides the accuracy of database query. For a higher accuracy of a full spectral matching algorithm, this paper presents a full spectral matching algorithm based on a Jaccard similarity coefficient (JSC). In order to satisfy the requirement of JSC, the first derivate of raw spectra should be computed, and a transformation process would transform negative values to 0 and positive values to 1, where 0 means the raw spectrum is descending in the according small region while 1 means the raw spectrum is ascending in the according small region. Therefore, the optimal resolution of this algorithm should be determined at first when it is used for the spectra