Automatic leaf segmentation using grey Wolf optimizer based neural network
Küçük Resim Yok
Tarih
2017
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This study proposes a hybrid neural network model for the segmentation of leaf images with various illumination conditions. Segmentation of images with different illumination conditions is a quite challenging process. In particular, the shadows and dark regions in the image can be quite misleading for traditional segmentation algorithms. Using a single feature or reviewing them in a single colour space may work for some images, but this approach does not work on the entire dataset that have different colour. For this reason, automatic segmentation method is proposed in this study by using components from four different colour spaces. Firstly, the image is converted into RGB, HSV, XYZ and YIQ channels. Then, B, S, Z and I components are used to train hybrid neural network. Grey wolf optimizer is used for neural network optimization. The segmentation results of proposed method are compared with the well-known segmentation algorithms and are more successful. The results of proposed method are that sensitivity is 99.66 %, specificity is 98.42 % and accuracy is 99.31 %. © 2017 IEEE.
Açıklama
21st International Conference on Electronics -- 19 June 2017 through 21 June 2017 -- 129782
Anahtar Kelimeler
grey Wolf optimizer, hybrid neural network, illumination condition, Leaf segmentation
Kaynak
Proceedings of the 21st International Conference on Electronics
WoS Q Değeri
Scopus Q Değeri
N/A
