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Identification of Pecan Weevils thro...

Oklahoma State University., Biosystems & Agricultural Engineering.

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Identification of Pecan Weevils through image processing.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Identification of Pecan Weevils through image processing./
Author:	Ashaghathra, Saleh M.
Description:	148 p.
Notes:	Source: Dissertation Abstracts International, Volume: 69-04, Section: B, page: 2444.
Contained By:	Dissertation Abstracts International69-04B.
Subject:	Engineering, Agricultural. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoeng/servlet/advanced?query=3307367
ISBN:	9780549560944

Identification of Pecan Weevils through image processing.
Ashaghathra, Saleh M.

Identification of Pecan Weevils through image processing. - 148 p.

Source: Dissertation Abstracts International, Volume: 69-04, Section: B, page: 2444.

Thesis (Ph.D.)--Oklahoma State University, 2008.

Scope and Method of Study. The scope of this study is to develop a recognition system that can serve in a wireless imaging network for monitoring pecan weevils. The recognition methods used in this study are based on template matching. Five recognition methods were implemented in this study; namely, Normalized crosscorrelation, Fourier descriptors, Zernike moments, String matching, and Regional properties. The training set consisted of 205 pecan weevils and the testing set included 30 randomly selected pecan weevils and 74 other insects which typically exist in pecan habitat.

ISBN: 9780549560944Subjects--Topical Terms:

1019504
Engineering, Agricultural.

Identification of Pecan Weevils through image processing.
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005 20100712
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020 $a 9780549560944
035 $a (UMI)AAI3307367
035 $a AAI3307367
040 $a UMI $c UMI
100 1 $a Ashaghathra, Saleh M. $3 1025238
245 1 0 $a Identification of Pecan Weevils through image processing.
300 $a 148 p.
500 $a Source: Dissertation Abstracts International, Volume: 69-04, Section: B, page: 2444.
502 $a Thesis (Ph.D.)--Oklahoma State University, 2008.
520 $a Scope and Method of Study. The scope of this study is to develop a recognition system that can serve in a wireless imaging network for monitoring pecan weevils. The recognition methods used in this study are based on template matching. Five recognition methods were implemented in this study; namely, Normalized crosscorrelation, Fourier descriptors, Zernike moments, String matching, and Regional properties. The training set consisted of 205 pecan weevils and the testing set included 30 randomly selected pecan weevils and 74 other insects which typically exist in pecan habitat.
520 $a Findings and Conclusions. It is found that Region-based methods are better in representing and recognizing biological objects such as insects. Moreover, different recognition rates are obtained at different order of Zernike moments. The optimum result among the tested orders of Zernike moments is found to be at order 3. The results also show that using different number of Fourier descriptors may not significantly increase the recognition rate of this method. The most robust and reliable recognition rate is achieved when the two recognition methods, namely, Zernike moments and Region properties are used in a combination. The results indicate that a positive match from either of these two independent tests would yield reliable results; therefore, 100% recognition could be achieved by adopting the proposed algorithm. In addition, the processing time for such recognition is 0.44 sec., on average.
590 $a School code: 0664.
650 4 $a Engineering, Agricultural. $3 1019504
650 4 $a Engineering, Electronics and Electrical. $3 626636
690 $a 0539
690 $a 0544
710 2 $a Oklahoma State University. $b Biosystems & Agricultural Engineering. $3 1025237
773 0 $t Dissertation Abstracts International $g 69-04B.
790 $a 0664
791 $a Ph.D.
792 $a 2008
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoeng/servlet/advanced?query=3307367