关键词: 预分割, 超像素集, 测地线距离, Ng-Jordan-Weiss（NJW）算法

Abstract: Spectral clustering algorithm has been widely used in image segmentation, however, traditional spectral clustering algorithms are susceptible to the effect of color image size and similarity measure. They create large amount of calculation and the poor segmentation result. In order to solve these two problems, this paper proposes a new spectral clustering segmentation algorithm based on geodesic characteristics of super pixel set. It uses the pre-segmentation to get the super set of pixels. Then it constructs a weighted graph, and uses the geodesic distance and color features to build a weight matrix. It uses NJW（Ng-Jordan-Weiss） algorithm to get the segmentation result. The experimental results show that the segmentation accuracy and computational complexity of the algorithm in this paper are improved substantially.

Key words: pre-segmentation, super pixel sets, geodesic distance, Ng-Jordan-Weiss（NJW） algorithm