An Inspection Method of Rice Milling Degree Based on Machine Vision and Gray-Gradient Co-occurrence Matrix

Abstract : A detection method of the rice milling degree was proposed based on machine vision with gray-gradient co-occurrence matrix. Using an experimental mill machine, different milling degree samples of rice were prepared. The rice kernel image of the different milling degree was get by a machine vision detecting system, then the texture features of the rice image were obtained by using gray-gradient co-occurrence matrix, at last the Fisher discriminate functions constructed using stepwise discriminate analysis were used to detect the milling degree of the rice samples. The testing results show that the average accuracy rate of the different milling degree detected using the method of 4 rice samples is 94.00%.
Type de document :
Communication dans un congrès
Daoliang Li; Yande Liu; Yingyi Chen. 4th Conference on Computer and Computing Technologies in Agriculture (CCTA), Oct 2010, Nanchang, China. Springer, IFIP Advances in Information and Communication Technology, AICT-344 (Part I), pp.195-202, 2011, Computer and Computing Technologies in Agriculture IV. 〈10.1007/978-3-642-18333-1_23〉
Liste complète des métadonnées

Littérature citée [8 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01559628
Contributeur : Hal Ifip <>
Soumis le : lundi 10 juillet 2017 - 17:28:46
Dernière modification le : mardi 18 juillet 2017 - 15:29:17
Document(s) archivé(s) le : mercredi 24 janvier 2018 - 18:19:23

Fichier

978-3-642-18333-1_23_Chapter.p...
Fichiers produits par l'(les) auteur(s)

Licence


Distributed under a Creative Commons Paternité 4.0 International License

Identifiants

Citation

Peng Wan, Changjiang Long. An Inspection Method of Rice Milling Degree Based on Machine Vision and Gray-Gradient Co-occurrence Matrix. Daoliang Li; Yande Liu; Yingyi Chen. 4th Conference on Computer and Computing Technologies in Agriculture (CCTA), Oct 2010, Nanchang, China. Springer, IFIP Advances in Information and Communication Technology, AICT-344 (Part I), pp.195-202, 2011, Computer and Computing Technologies in Agriculture IV. 〈10.1007/978-3-642-18333-1_23〉. 〈hal-01559628〉

Partager

Métriques

Consultations de la notice

82

Téléchargements de fichiers

31