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 :
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