Open AccessIMPLEMENTATION OF GENETIC ALGORITHM BASED ARTIFICIAL NEURAL NETWORK TO IDENTIFY VEGETABLES WITH PHYSIOLOGICAL DISEASES
Author(s) -
Bibhu Prasad,
Ashima Sindhu Mohanty,
Ami Kumar Parida
Publication year - 2013
Publication title -
international journal of smart sensors and ad hoc networks
Language(s) - English
Resource type - Journals
ISSN - 2248-9738
DOI - 10.47893/ijssan.2013.1200
Subject(s) - artificial neural network , artificial intelligence , identification (biology) , genetic algorithm , computer science , roundness (object) , pattern recognition (psychology) , machine learning , engineering , biology , botany , mechanical engineering
We synthetically applied computer vision, genetic algorithm and artificial neural network technology to automatically identify the vegetables (tomatoes) that had physiological diseases. Initially tomatoes’ images were captured through a computer vision system. Then to identify cavernous tomatoes, we analyzed the roundness and detecteddeformed tomatoes by applying the variation of vegetable’s diameter. Later, we used a Genetic Algorithm (GA) based artificial neural network (ANN). Experiments show that the above methods can accurately identify vegetables’ shapes and meet requests of classification; the accuracy rate for the identification for vegetables with physiological diseases was up to 100%. [Nature and Science. 2005; 3(2):52-58].