Using Quadtree Algorithm for Improving Fuzzy C-means Method in Image Segmentation
Image segmentation is an essential processing step for much image application and there are a large number of segmentation techniques. A new algorithm for image segmentation called Quad tree fuzzy c-means (QFCM) is presented I this work. The key idea in our approach is a Quad tree function combined with fuzzy c-means algorithm. In this article we also discuss the advantages and disadvantages of other image segmenting methods like: k-means, c-means, and blocked fuzzy c-means. Different experimental results on several images in this article show that the proposed method significantly increases the accuracy and speed of image segmentation
Keywords: Image Segmentation; Fuzzy Clustering; Quadtree ; C-means, K-means
Download Full-Text
ABOUT THE AUTHORS
Zahra Ghorbanzad
Faculty of Engineering, Islamic Azad University Science and Research Branch Tehran, Iran
Farshid Babapour
Faculty of Engineering, Islamic Azad University Science and Research Branch Tehran, Iran
Zahra Ghorbanzad
Faculty of Engineering, Islamic Azad University Science and Research Branch Tehran, Iran
Farshid Babapour
Faculty of Engineering, Islamic Azad University Science and Research Branch Tehran, Iran
