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 :
بازگشت