Abstract : As the identification of surface defects is very important in fruit automatic detection, a new method for the detection of fruit surface defects based on fractal dimension is suggested. In this method, fruit image was collected using computer vision system. The fractal dimension of fruit image was calculated by an improved ‘box dimension’. The fruit fractal dimension reflects the three dimensional characteristics of the fruit as well as information of the fruit surface. The detection of surface defects of fruits was performed according to a given threshold of fruit image fractal dimension. The results on Fuji apple fruits showed that the improved ‘box dimension’ method was effective and reliable in the detection of fruit defects for its improvement in the accuracy in the calculation of the fractal dimension.
Daoliang Li; Yande Liu; Yingyi Chen. 4th Conference on Computer and Computing Technologies in Agriculture (CCTA), Oct 2010, Nanchang, China. Springer, IFIP Advances in Information and Communication Technology, AICT-344 (Part I), pp.547-554, 2011, Computer and Computing Technologies in Agriculture IV. 〈10.1007/978-3-642-18333-1_65〉
https://hal.inria.fr/hal-01559587
Contributeur : Hal Ifip
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Soumis le : lundi 10 juillet 2017 - 17:28:15
Dernière modification le : mardi 18 juillet 2017 - 15:29:46
Document(s) archivé(s) le : mercredi 24 janvier 2018 - 18:06:32
Yongxiang Sun, Yong Liang, Qiulan Wu. Detection of Surface Defects of Fruits Based on Fractal Dimension. Daoliang Li; Yande Liu; Yingyi Chen. 4th Conference on Computer and Computing Technologies in Agriculture (CCTA), Oct 2010, Nanchang, China. Springer, IFIP Advances in Information and Communication Technology, AICT-344 (Part I), pp.547-554, 2011, Computer and Computing Technologies in Agriculture IV. 〈10.1007/978-3-642-18333-1_65〉. 〈hal-01559587〉
