DocumentCode
2041502
Title
Peanut Shape Recognition Based on Fourier Descriptor
Author
Chen Hong ; Zeng Chuanhua ; Ding Youchun
Author_Institution
Eng. & Technol. Coll., Huazhong Agric. Univ., Wuhan
fYear
2009
fDate
23-24 May 2009
Firstpage
1
Lastpage
4
Abstract
A sort of software for peanut shape identification based on artificial neural network was developed. Images of peanut which is advantageous for carries on the characteristic extraction were acquired by means of red component extraction, filter, image division, edge examination, and so on. The method to describe the shape of irregular peanut was studied, in which the Fourier transform and Fourier inverse transform were applied. It was concluded that the first thirteen harmonics of the Fourier descriptor were enough to represent the primary shape of peanut, The method achieved an accuracy of 90% for oblong peanuts, 93.3% for simple peanuts, 96.7% for trilateral peanuts, 100% for elliptic peanuts and 93.3% for circular peanuts.
Keywords
Fourier transforms; edge detection; feature extraction; neural nets; object recognition; Fourier descriptor; Fourier inverse transform; Fourier transform; artificial neural network; edge examination; image division; peanut shape recognition; red component extraction; Agricultural engineering; Agricultural products; Color; Computer vision; Educational institutions; Electronic mail; Fourier transforms; Kernel; Materials testing; Shape;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems and Applications, 2009. ISA 2009. International Workshop on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-3893-8
Electronic_ISBN
978-1-4244-3894-5
Type
conf
DOI
10.1109/IWISA.2009.5073005
Filename
5073005
Link To Document