Identifying apple surface defects based on gabor features and SVM using machine vision

Wenqian Huang; Chi Zhang; Baihai Zhang

doi:10.1007/978-3-642-27275-2_39

Identifying apple surface defects based on gabor features and SVM using machine vision

Wenqian Huang^*, Chi Zhang, Baihai Zhang

^*Corresponding author for this work

School of Automation

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

11 Citations (Scopus)

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.

Original language	English
Title of host publication	Computer and Computing Technologies in Agriculture V - 5th IFIP TC 5/SIG 5.1 Conference, CCTA 2011, Proceedings
Pages	343-350
Number of pages	8
Edition	PART 3
DOIs	https://doi.org/10.1007/978-3-642-27275-2_39
Publication status	Published - 2012
Event	5th International Conference on Computer and Computing Technologies in Agriculture, CCTA 2011 - Beijing, China Duration: 29 Oct 2011 → 31 Oct 2011

Publication series

Name	IFIP Advances in Information and Communication Technology
Number	PART 3
Volume	370 AICT
ISSN (Print)	1868-4238

Conference

Conference	5th International Conference on Computer and Computing Technologies in Agriculture, CCTA 2011
Country/Territory	China
City	Beijing
Period	29/10/11 → 31/10/11

Keywords

Gabor wavelet
SVM
apple quality grading
defect identification

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10.1007/978-3-642-27275-2_39

Cite this

Huang, W., Zhang, C., & Zhang, B. (2012). Identifying apple surface defects based on gabor features and SVM using machine vision. In Computer and Computing Technologies in Agriculture V - 5th IFIP TC 5/SIG 5.1 Conference, CCTA 2011, Proceedings (PART 3 ed., pp. 343-350). (IFIP Advances in Information and Communication Technology; Vol. 370 AICT, No. PART 3). https://doi.org/10.1007/978-3-642-27275-2_39

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title = "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.",

keywords = "Gabor wavelet, SVM, apple quality grading, defect identification",

author = "Wenqian Huang and Chi Zhang and Baihai Zhang",

year = "2012",

doi = "10.1007/978-3-642-27275-2_39",

language = "English",

isbn = "9783642272745",

series = "IFIP Advances in Information and Communication Technology",

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pages = "343--350",

booktitle = "Computer and Computing Technologies in Agriculture V - 5th IFIP TC 5/SIG 5.1 Conference, CCTA 2011, Proceedings",

edition = "PART 3",

note = "5th International Conference on Computer and Computing Technologies in Agriculture, CCTA 2011 ; Conference date: 29-10-2011 Through 31-10-2011",

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Huang, W, Zhang, C & Zhang, B 2012, Identifying apple surface defects based on gabor features and SVM using machine vision. in Computer and Computing Technologies in Agriculture V - 5th IFIP TC 5/SIG 5.1 Conference, CCTA 2011, Proceedings. PART 3 edn, IFIP Advances in Information and Communication Technology, no. PART 3, vol. 370 AICT, pp. 343-350, 5th International Conference on Computer and Computing Technologies in Agriculture, CCTA 2011, Beijing, China, 29/10/11. https://doi.org/10.1007/978-3-642-27275-2_39

Identifying apple surface defects based on gabor features and SVM using machine vision. / Huang, Wenqian; Zhang, Chi; Zhang, Baihai.
Computer and Computing Technologies in Agriculture V - 5th IFIP TC 5/SIG 5.1 Conference, CCTA 2011, Proceedings. PART 3. ed. 2012. p. 343-350 (IFIP Advances in Information and Communication Technology; Vol. 370 AICT, No. PART 3).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Zhang, Chi

AU - Zhang, Baihai

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AB - 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.

KW - Gabor wavelet

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Identifying apple surface defects based on gabor features and SVM using machine vision

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Keywords

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