Title :
Apple Defect Detection Using Statistical Histogram Based Fuzzy C-Means Algorithm
Author :
Moradi, Ghobad ; Shamsi, Mousa ; Sedaaghi, Mohammad Hossein ; Moradi, Setareh
Author_Institution :
Islamic Azad Univ., Kermanshah, Iran
Abstract :
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.
Keywords :
computer vision; feature extraction; food products; image colour analysis; image segmentation; object detection; production engineering computing; quality control; statistical analysis; ACM algorithm; SHFCM algorithm; apple defect detection; apple quality determination; apple skin color defects; color space; computer vision; fruit shape extraction; image partition; image processing; image segmentation; red-green-blue; statistical histogram based fuzzy c-means algorithm; Classification algorithms; Clustering algorithms; Color; Histograms; Image color analysis; Image segmentation;
Conference_Titel :
Machine Vision and Image Processing (MVIP), 2011 7th Iranian
Conference_Location :
Tehran
Print_ISBN :
978-1-4577-1533-4
DOI :
10.1109/IranianMVIP.2011.6121573