抄録
FCM-type linear fuzzy clustering performs FCM clustering by replacing the point prototypes (mean vectors) with linear prototypes such as lines and linear varieties, and achieves local PCA for extracting intrinsic local linear sub-structures. This paper proposes an extended linear fuzzy clustering model for extracting cross-shape clusters formed by two lines. In the new FCM-type clustering model, each crossing prototype composed of two lines is recognized in a single process by considering local coordinate rotation. After rotation around the intersection of two lines, cross-shape prototype identification is achieved in a similar procedure with the conventional linear fuzzy clustering models where the goal is to identify a single basis vector for each prototype.
