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Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In this paper, a new method of inspecting fruit quality is proposed based on color image processing. After an image of fruits is taken, white balance is performed. Then the image is transferred from the RGB color model to the HSI color model. Its simplified histograms of hue H and saturation S are calculated as the input of a designed BP network. The output of the BP network is the quality description of the inspected fruits. The number of neurons in the intermediate layer is optimized according to generated error of the BP network. After training, the quality of fruits is inspected by the BP network according to the simplified histograms of H and S of their color image. Experiments are conducted with the quality inspection of bananas. Experiment results show the feasibility and reliability of proposed method.