The following information was submitted:
Transactions: INTERNATIONAL JOURNAL of MATHEMATICS AND COMPUTERS IN SIMULATION
Transactions ID Number: 19-303
Full Name: Marius-Constantin Popescu
Position: Associate Professor
Age: ON
Sex: Male
Address: CRAIOVA, STR. PALTINIS, NR. 59, BL. K-7, AP. 2
Country: ROMANIA
Tel: 0745438287
Tel prefix: 004
Fax: +40251435255
E-mail address: popescu.marius.c@gmail.com
Other E-mails: popescu_ctin2006@yahoo.com
Title of the Paper: New Techniques of Products Analysis
Authors as they appear in the Paper: Marius Buzera, Marius-Constantin Popescu, Nikos E. Mastorakis, Jean-Octavian Popescu
Email addresses of all the authors: marius.buzera@ieee.org, popescu.marius.c@gmail.com, mastor@wses.org, popescu_jean2005@yahoo.com
Number of paper pages: 8
Abstract: researches throughout the past few years, having as a goal the automatic classification of products, via calculus systems implementation, as well as machine vision techniques, and artificial intelligence field methods, have lead to very promising results. Together with the colour, shape is one of the most important parameters of vegetal products. Thus, it helps one learn further information on the integrity of products, information which can be used in their classification, while taking the shape into consideration. Using them allowed for the assessment of some parameters such as shape, colour and the integrity degree of the products analyzed, having much more superior results than the classical classification installations. Still, due to these techniques particularities, the classification process implies going through some more phases. Both the experimental methodology for classifying vegetal products and some original algorithms are presented in this paper. To !
classify the shape it has been developed back-propagation feed-forward artificial neural network, and for colour a fuzzy algorithm. In order to test these techniques, an experimental device was created to allow a video inspection of products, some of the conclusions being presented in this material.
Keywords: machine vision, shape, colour, classification, image processing, neural network, fuzzy logic
EXTENSION of the file: .pdf
Special (Invited) Session: Pumping Station Automatic Monitoring System
Organizer of the Session: 634-509
How Did you learn about congress:
IP ADDRESS: 79.117.156.51
