Chunshi Sha

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Dominant sets clustering is a promising clustering approach based on a graph-theoretic concept of a cluster. With the pairwise similarity matrix of data as input, dominant sets clustering determines the number of clusters by itself and possesses some other nice properties. However, the original dominant sets clustering algorithm is sensitive to similarity(More)
In this paper, we proposed a gray level-median histogram based two-dimensional (2D) Otsu's method, which is efficient and robust to noise. In our method, we use gray level-median instead of gray level-mean to build 2D histogram. We also proposed a new method to process the edge and noise regions to reduce noise and obtain more clear edges. In order to(More)
In this paper we study the recognition of repetitive patterns. While SIFT (Scale-Invariant Feature Transform) is shown to be very distinctive in feature representation and matching, it is hindered from producing better performance in building recognition as repetitive structures in building images make distance ratio criterion not suitable in matching.(More)
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