A Novel Neural Networks-Based Texture Image Processing Algorithm for Orange Defects Classification.
Year: 2016
Type: article
Abstract: In this paper is proposed, implemented and evaluated a novel radial basis probabilistic neuralnetwork (RBPNN) based classification algorithm for classification fruit surface defects in color andtexture of a very important fruit as orange. The proposed algorithm takes orange images as inputsthen the texture and gray features of defect area are extracted by computing a gray level co-occurrencematrix and the defect areas are classified through an RBPNN-based classifier. Theconducted experiments and the results reveal as the classification accuracy achieved is up to 88%.
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2592436748