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Apple Defect Detection Using Statistical Histogram Based Fuzzy C-Means Algorithm

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4 Author(s)
Moradi, G. ; Islamic Azad Univ., Kermanshah, Iran ; Shamsi, M. ; Sedaaghi, M.H. ; Moradi, S.

Image segmentation is one of the important and complicated processes among image processing and computer vision algorithm. Its purpose is to partition an input image into disjoint parts. In this article an important application of image processing in determination of apple quality is studied, and an automatic algorithm is proposed in order to determine apples skin color defects. First, this image is converted from RGB to color space L*a*b*. Then fruit shape is extracted by ACM algorithm. Finally, the image has segmented using SHFCM algorithm. Experimental results on the acquired images show that both FCM and SHFCM spend the same iterations to accomplish the segmentation process and get the same results. However, the proposed SHFCM algorithm consumes less time than the standard FCM algorithm. Accuracy of the proposed algorithm on the acquired images is 91% and 96% for healthy pixels and defected ones, respectively.

Published in:

Machine Vision and Image Processing (MVIP), 2011 7th Iranian

Date of Conference:

16-17 Nov. 2011