Identifying Apple Surface Defects Based on Gabor Features and SVM Using Machine Vision

Abstract : In this paper, a novel method to recognize defect regions of apples based on Gabor wavelet transformation and SVM using machine vision is proposed. The method starts with background removal and object segmentation by threshold. Texture features are extracted from each segmented object by using Gabor wavelet transform, and these features are introduced to support vector machines (SVM) classifiers. Experimental results exhibit correctly recognized 85% of the defect regions of apples.
Type de document :
Communication dans un congrès
Daoliang Li; Yingyi Chen. 5th Computer and Computing Technologies in Agriculture (CCTA), Oct 2011, Beijing, China. Springer, IFIP Advances in Information and Communication Technology, AICT-370 (Part III), pp.343-350, 2012, Computer and Computing Technologies in Agriculture V. 〈10.1007/978-3-642-27275-2_39〉
Liste complète des métadonnées

Littérature citée [10 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01361158
Contributeur : Hal Ifip <>
Soumis le : mardi 6 septembre 2016 - 17:11:30
Dernière modification le : mardi 6 septembre 2016 - 17:40:16
Document(s) archivé(s) le : mercredi 7 décembre 2016 - 14:22:22

Fichier

978-3-642-27275-2_39_Chapter.p...
Fichiers produits par l'(les) auteur(s)

Licence


Distributed under a Creative Commons Paternité 4.0 International License

Identifiants

Citation

Wenqian Huang, Chi Zhang, Baihai Zhang. Identifying Apple Surface Defects Based on Gabor Features and SVM Using Machine Vision. Daoliang Li; Yingyi Chen. 5th Computer and Computing Technologies in Agriculture (CCTA), Oct 2011, Beijing, China. Springer, IFIP Advances in Information and Communication Technology, AICT-370 (Part III), pp.343-350, 2012, Computer and Computing Technologies in Agriculture V. 〈10.1007/978-3-642-27275-2_39〉. 〈hal-01361158〉

Partager

Métriques

Consultations de la notice

130

Téléchargements de fichiers

117