@inproceedings{88402d435ce94159809a7382aa2cfa08,
title = "An adaptive path classification algorithm for a pepper greenhouse sprayer",
abstract = "An adaptive path classification algorithm for a pepper greenhouse sprayer working under variable outdoor lighting conditions is described. 22 color features transformations specialized in soil-leafage discrimination extracted from the RGB and HSV 24-bit color images were created. 'Judges Vote', an innovative supervised learning methodology based on decision tree CART, was developed to classify pixels according to their color features into {"}Path{"} and {"}Non-Path{"} classes. Optimal CART feature selection was implemented by creating several single level trees. Image processing routines (including segmentation, erosion and dilution) were integrated. 12 features were selected from the original 22. Classification tests for seven random daylight videos resulted in 92% correct detection as compared to 89% correct classification obtained with regular CART classification.",
keywords = "Adaptive, Classification, Color, Image processing, Sprayer, Vision",
author = "Itamar Dar and Yael Edan and Avital Bechar",
year = "2011",
month = jan,
day = "1",
language = "English",
isbn = "9781618391568",
series = "American Society of Agricultural and Biological Engineers Annual International Meeting 2011, ASABE 2011",
publisher = "American Society of Agricultural and Biological Engineers",
pages = "288--302",
booktitle = "American Society of Agricultural and Biological Engineers Annual International Meeting 2011, ASABE 2011",
address = "United States",
note = "American Society of Agricultural and Biological Engineers Annual International Meeting 2011 ; Conference date: 07-08-2011 Through 10-08-2011",
}