Bilgisayar Bilimleri

Bilgisayar Bilimleri

The Texture Feature Extraction of Agricultural Field Images by HOG Algorithms and Soil Moisture Estimation based on the Texture Features

Yazarlar: Emrullah ACAR, Mehmet Siraç ÖZERDEM

Cilt 1 , Sayı 1 , 2016 , Sayfalar 1 - 7

Konular:Bilgisayar Bilimleri, Bilgi Sistemleri

Anahtar Kelimeler:Soil Moisture Estimation,Image Processing,Classification,LP,K-NN,HOG

Özet: Knowing the value of soil surface moisture in the agricultural areas are very important in many ways such as minimizing the harmful effects of drought cases, preventing salinity caused by over watering, protecting agricultural lands and using the irrigation system efficiently. The main purpose of this study is that determining a relationship between measurements of local soil moisture and images in agricultural Mardin region and prediction of soil moisture with the determined relationship. The images are derived from TARBIL (http://www.tarbil.org) database. The texture feature vectors are extracted from the images by using Histogram of Oriented Gradients (HOG) algorithm. The obtained feature vectors are then classified into three (much, middle and little) groups by using k-Nearest Neighbor (k-NN) and Multilayer Perceptron (MLP) classifiers. 

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@article{2016, title={The Texture Feature Extraction of Agricultural Field Images by HOG Algorithms and Soil Moisture Estimation based on the Texture Features}, volume={1}, number={1–7}, publisher={Bilgisayar Bilimleri}, author={Emrullah ACAR,Mehmet Siraç ÖZERDEM}, year={2016} }
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Emrullah ACAR,Mehmet Siraç ÖZERDEM. (2016). The Texture Feature Extraction of Agricultural Field Images by HOG Algorithms and Soil Moisture Estimation based on the Texture Features (Vol. 1). Vol. 1. Bilgisayar Bilimleri.
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Emrullah ACAR,Mehmet Siraç ÖZERDEM. The Texture Feature Extraction of Agricultural Field Images by HOG Algorithms and Soil Moisture Estimation Based on the Texture Features. no. 1–7, Bilgisayar Bilimleri, 2016.
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