Abstract
Image segmentation is the basis of image processing and an important technology in computer vision and other fields. With the continuous development of computer technology, image segmentation also presents a new look. Therefore, the research on image segmentation methods has far-reaching significance to make it better serve people's lives. The quality of image segmentation results will directly affect the quality of subsequent applications such as image processing. The Fuzzy C-means Clustering (FCM) algorithm also has certain defects or deficiencies. The traditional FCM algorithm is divided based on the grayscale of the image pixels, which is unreasonable to some extent. In order to speed up the convergence speed of the algorithm and improve the noise resistance of the algorithm, this paper selects an FCM based on spatial information for improvement, and proposes an improved FCM segmentation algorithm. The experimental results show that the improved algorithm has high segmentation efficiency, high segmentation accuracy and strong anti-noise.
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