Application of back propagation diagnostic model for fruit maturity classification

Case Jatropha curcas

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Recently, studies on biodiesel alternative have attracted researchers to find another agricultural solution for bio energy. One of the alternatives is biodiesel from Jatropha curcas fruits. The quality of the fruit is largely depends on type of defects, skin color and size of the fruit. In this research, we develop an image recognition system to identify the level of maturity of Jatropha curcas fruit and classify them into various categories. A back propagation diagnosis model(BPDM) is adopted to recognize the image of the matured fruits. Color indices associated with image pixels are used as input. As a result, the developed BPMD can give 95% accuracy based on samples of twenty-seven images. It can be ascertained that our proposed BPDM can achieved its performance function.

Original languageEnglish
Pages (from-to)134-140
Number of pages7
JournalAustralian Journal of Basic and Applied Sciences
Volume5
Issue number3
Publication statusPublished - Mar 2011

Fingerprint

Fruits
Backpropagation
Biodiesel
Color
Image recognition
Skin
Pixels
Defects

Keywords

  • Back propagation diagnostic model
  • Image recognition
  • Maturity
  • Neural network

ASJC Scopus subject areas

  • General

Cite this

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title = "Application of back propagation diagnostic model for fruit maturity classification: Case Jatropha curcas",
abstract = "Recently, studies on biodiesel alternative have attracted researchers to find another agricultural solution for bio energy. One of the alternatives is biodiesel from Jatropha curcas fruits. The quality of the fruit is largely depends on type of defects, skin color and size of the fruit. In this research, we develop an image recognition system to identify the level of maturity of Jatropha curcas fruit and classify them into various categories. A back propagation diagnosis model(BPDM) is adopted to recognize the image of the matured fruits. Color indices associated with image pixels are used as input. As a result, the developed BPMD can give 95{\%} accuracy based on samples of twenty-seven images. It can be ascertained that our proposed BPDM can achieved its performance function.",
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AB - Recently, studies on biodiesel alternative have attracted researchers to find another agricultural solution for bio energy. One of the alternatives is biodiesel from Jatropha curcas fruits. The quality of the fruit is largely depends on type of defects, skin color and size of the fruit. In this research, we develop an image recognition system to identify the level of maturity of Jatropha curcas fruit and classify them into various categories. A back propagation diagnosis model(BPDM) is adopted to recognize the image of the matured fruits. Color indices associated with image pixels are used as input. As a result, the developed BPMD can give 95% accuracy based on samples of twenty-seven images. It can be ascertained that our proposed BPDM can achieved its performance function.

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