One of the most important topics in image processing is edge detection. Many methods have been\r\nproposed for this end but most of them have weak performance in noisy images because noise pixels are\r\ndetermined as edge. In this paper, two new methods are represented based on Hierarchical Adaptive Neuro\r\nFuzzy Systems (HANFIS). Each method consists of desired number of HANFIS operators that receive the\r\nvalue of some neighbouring pixels and decide central pixel is edge or not. Simple train images are used in\r\norder to set internal parameters of each HANFIS operator. The presented methods are evaluated by some\r\ntest images and compared with several popular edge detectors. The experimental results show that these\r\nmethods are robust against impulse noise and extract edge pixels exactly.
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