Browsing by Author "YIN, PY"

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A NEW NONITERATIVE APPROACH FOR CLUSTERING
(1994-02-01)
YIN, PY
;
CHEN, LH
;
資訊工程學系
;
Department of Computer Science
In this paper, a new non-iterative clustering method is proposed. It consists of two passes. In the first pass, the mean distance from one object to its nearest neighbor is estimated. Based on this distance, those noises far away from objects are extracted and removed. In the second pass, the mean distance from the remaining objects to their nearest neighbors is computed. Based on the distance, all the intrinsic clusters are then found. The proposed method is non-iterative and can automatically determine the number of clusters. Experimental results also show that the partition generated by the proposed method is more reasonable than that of the well-known c-means algorithm in many complicated object distributions.
RANDOM-SAMPLING THRESHOLDING - A NEW APPROACH TO MULTILEVEL THRESHOLDING
(1993-12-01)
YIN, PY
;
CHEN, LH
;
資訊工程學系
;
Department of Computer Science
In this paper, a new approach to multilevel thresholding is proposed. First, the approach uniformly spreads some coarse thresholds over the gray-level range. Then, an adjusting process is applied repeatedly until a certain stopping criterion is reached. In the process, some pixels are first randomly sampled. Then, those coarse thresholds are finely adjusted according to the distribution of their neighborhood in the histogram formed by the randomly sampled pixels. The proposed method can automatically determine the number of thresholds. Furthermore, if the number of the resulting thresholds is not sufficient under a certain sense, the proposed method can be iteratively applied, based on the previous results, to get more thresholds. Experimental results also show that the performance of the proposed method is comparable to that of the recent method presented by Lim.