A NOVEL EDGE DETECTION METHOD USING K-MEANS CLUSTERING - Mohammed Khalaf, Walaa; Al-Majdi, Kadhum; Hashim Hamed, Noor (Journal of Engineering and Sustainable Development, 2016)
In this paper, a new approach is introduced to detect the edges of any kind of grayscale image by using the k-means clustering algorithm, where three novel features are proposed by taking the advantage of the similarity of the image pixel with its eight surrounding neighbors through feeding these features as attributes to the clustering system. This method of edge detection does not use either any smoothing filter or threshold values. The experimental results show that an acceptable detection of the edges is done.