Detectar e classificar castanhas de caju, tipo inteiro branco, através de rede neural artificial

Translated title of the contribution: Recognition and classification of White Wholes (WW) grade cashew kernel using artificial neural networks

Narendra Veranagouda Ganganagowdar, Hareesha Katiganere Siddaramappa

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

A novel intelligent automated model to recognize and classify a cashew kernels using Artificial Neural Network (ANN). The model primarily intends to work on two phases. The phase one, built with a proposed method to extract features, which includes 16 morphological features and also 24 color features from the input cashew kernel images. In phase two, a Multilayer Perceptron ANN is being used to recognize and classify the given white wholes grades using back propagation learning algorithm. The proposed method achieves a classification accuracy of 88.93%. This study also reveals that the combination of morphological and color features outperforms rather using any one set of features separately to grade cashew kernels.

Translated title of the contributionRecognition and classification of White Wholes (WW) grade cashew kernel using artificial neural networks
Original languagePortuguese
Pages (from-to)145-155
Number of pages11
JournalActa Scientiarum - Agronomy
Volume38
Issue number2
DOIs
Publication statusPublished - 01-04-2016

All Science Journal Classification (ASJC) codes

  • Agronomy and Crop Science

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