DocumentCode
1694231
Title
Produce recognition system using data mining algorithm
Author
Chaw, J.K. ; Mokji, M.M.
Author_Institution
Dept. of Microelectron. & Comput. Eng., Univ. Teknol. Malaysia, Skudai, Malaysia
fYear
2012
Firstpage
39
Lastpage
43
Abstract
Produce recognition system is a system that can categorize types of vegetables and fruits based on features extracted from the images. However, there are numerous features that can be extracted from fruits and vegetables such as colour, texture and shape. As a result, it is effort consuming to identify suitable features ad hoc. Thus, data mining is required to discover the most discriminative features for recognition. This paper aims to extend the usage of data mining algorithm to image domain. Data mining algorithm is preferred to other feature selection algorithms because it discovers nuggets of knowledge that can be understood by human whereas classic feature selection techniques provide outputs that can only be managed by learning algorithms.
Keywords
agricultural products; data mining; feature extraction; image colour analysis; image texture; learning (artificial intelligence); shape recognition; data mining algorithm; extracted features; feature selection algorithms; fruits; image domain; learning algorithms; produce recognition system; vegetables; WEKA; data mining; produce recognition system;
fLanguage
English
Publisher
ieee
Conference_Titel
Control System, Computing and Engineering (ICCSCE), 2012 IEEE International Conference on
Conference_Location
Penang
Print_ISBN
978-1-4673-3142-5
Type
conf
DOI
10.1109/ICCSCE.2012.6487112
Filename
6487112
Link To Document