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Title: Automatic fruits identification system using hybrid technique
Authors: Aibinu, Abiodun M.
Salami, Momoh-Jimoh E.
Shafie, Amir A.
Hazali, Norazlanshah
Termidzi, N.
Keywords: Artificial Neural Network (ANN)
Fruits Images
Fourier Descriptors
Issue Date: 17-Jan-2011
Publisher: IEEE
Citation: Aibinu, A. M., Salami, M. J. E., Shafie, A. A., Hazali, N., & Termidzi, N. (2011, January). Automatic fruits identification system using hybrid technique. In 2011 Sixth IEEE International Symposium on Electronic Design, Test and Application (pp. 217-221). IEEE.
Abstract: In this work, a combination of artificial neural network (ANN), Fourier descriptors (FD) and spatial domain analysis (SDA) has been proposed for the development of an automatic fruits identification and sorting system. Fruits images are captured using digital camera inclined at different angles to the horizontal. Segmentation is used for the classification of the preprocessed images into two non-overlapping clusters from which shape boundary and signatures are estimated using FD and SDA technique. Furthermore, color information obtained from the extracted red-green-blue color components of the fruits images during ANN training process is used in accurately detecting the color of such a fruit. The two independent paths are then combined for fruits sorting and identification purposes. The performance of the developed hybrid system has been evaluated at three different angles of camera inclination from which an accuracy of 99:1% was obtained.
URI: 10.1109/DELTA.2011.47
Appears in Collections:Research Articles

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