Fruit defect detection from color images using ACM and MFCM algorithms

Segmentation of an image into its components plays an important role in most of the image processing applications. In this article an important application of image processing in determination of fruit quality is studied, and an automatic algorithm is proposed in order to determine fruits skin color...

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Bibliographic Details
Main Authors: Moradi, G., Shamsi, M., Sedaghi, M. H., Alsharif, M. R.
Format: Conference Proceeding
Language:English
Subjects:
active contour model
defect detection
fruit color image
fuzzy c-means
Image segmentation
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Summary:Segmentation of an image into its components plays an important role in most of the image processing applications. In this article an important application of image processing in determination of fruit quality is studied, and an automatic algorithm is proposed in order to determine fruits skin color defects. Removing of image background and extraction of fruit shape, exactly, at presence of shadow and complex background is considered as an important preprocessing stage. In proposed algorithm at first, background in image is omitted by using active counter model (ACM) algorithm. Finally, the image is segmented using modified FCM (MFCM) algorithm. Experimental results on fruit color images show that proposed algorithm increases accuracy and speed of fruit skin defect detection, considerably.
ISSN:2159-2047
2159-2055
DOI:10.1109/ICEDSA.2011.5959033