Toward an Automatic Parameterization System for the Classification of Persian Lemons Using Image-Processing Techniques Articles uri icon

authors

  • POSADA GOMEZ, RUBEN
  • VILLANUEVA, DANIEL
  • GONZALEZ CARRASCO, ISRAEL
  • GARCIA CRESPO, ANGEL
  • AGUILAR LASSERRE, ALBERTO
  • MARTÍNEZ SIBAJA, ALBINO

publication date

  • August 2015

start page

  • 345

end page

  • 356

issue

  • 4

volume

  • 38

International Standard Serial Number (ISSN)

  • 0145-8876

Electronic International Standard Serial Number (EISSN)

  • 1745-4530

abstract

  • The technological innovation has made significant progress that has affected almost all industrial technology and computer science areas. In the agribusiness sector, and specifically on the production of the Persian lemon, the control of product quality is essential; for this purpose, detailed information about the morphology and color characteristics is required to obtain. The aim of this paper is to present an automatic parameterization and classification system for agricultural engineering applications with easy operation, high mobility and innovative techniques based on digital image processing. This system is able to get the color and shape through the analysis of morphometric and colorimetric characteristics of Persian lemon in a preset scene. The classification system scans the surface of a lemon 360 degrees through multistage architecture components. With this system, the authors evaluate the morphometric and colorimetric variations using statistical data of positioning in the RGB channels of an image. Practical ApplicationsFor the agricultural industry, it is very important to improve the quality of agricultural products. In this proposal, the authors present a system for the classification of Persian lemons through automatic parameterization and image-processing techniques, generating products of highest quality and also facilitating energy savings for the industry. Moreover, the image-processing-based systems can also be used as a monitoring tool that facilitates visual inspection for the classification process, improving the final quality of the products and optimizing the manufacturing process.