Research on Improved K-means Image Segmentation Algorithm Based on HSV Space

Aiming at the defects that K-means algorithm is sensitive to the initial parameters and the segmentation effect is not ideal in image segmentation, this paper proposes an improved K-means segmentation algorithm. Firstly, the original image is converted from RGB space to HSV space, then the original image is filtered, and the outlier search algorithm is run to exclude outliers. Finally, K-means clustering image segmentation is carried out. Experimental results show that compared with the traditional K-means algorithm, the improved K-means segmentation algorithm can not only reduce the time complexity, but also achieve better image segmentation effect.