Online picture fuzzy clustering: A new approach for real-time fuzzy clustering on picture fuzzy sets

Online clustering plays an important roles in real-time clustering. In this paper, an innovative algorithm to online picture fuzzy clustering is proposed. Firstly, we calculate parameter for each element added for each steam for initialization. This step saves a lot time because of re-randomizing the initial of all data and calculating it through steps. Finally, we employ the iteration of picture fuzzy clustering for all data to partition clusters until getting ended condition. Experiments point out that the proposed algorithm has better run-time with trivial quality reduction.