Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Jim Z. C. Lai"'
Publikováno v:
Pattern Recognition. 46:2538-2547
In this paper, we present a rough k-means clustering algorithm based on minimizing the dissimilarity, which is defined in terms of the squared Euclidean distances between data points and their closest cluster centers. This approach is referred to as
Autor:
Tsung-Jen Huang, Jim Z. C. Lai
Publikováno v:
Information Sciences. 181:1722-1734
In this paper, a new algorithm is developed to reduce the computational complexity of Ward's method. The proposed approach uses a dynamic k-nearest-neighbor list to avoid the determination of a cluster's nearest neighbor at some steps of the cluster
Autor:
Tsung-Jen Huang, Jim Z. C. Lai
Publikováno v:
Pattern Recognition. 43:1954-1963
In this paper, we present a fast global k-means clustering algorithm by making use of the cluster membership and geometrical information of a data point. This algorithm is referred to as MFGKM. The algorithm uses a set of inequalities developed in th
Publikováno v:
Pattern Recognition. 42:2551-2556
In this paper, we present a fast k-means clustering algorithm (FKMCUCD) using the displacements of cluster centers to reject unlikely candidates for a data point. The computing time of our proposed algorithm increases linearly with the data dimension
Autor:
Yi-Ching Liaw, Jim Z. C. Lai
Publikováno v:
Pattern Recognition. 42:3065-3070
In this paper, a novel encoding algorithm for vector quantization is presented. Our method uses a set of transformed codewords and partial distortion rejection to determine the reproduction vector of an input vector. Experimental results show that ou
Publikováno v:
Signal Processing. 89:1115-1120
In this paper, we present a fast block matching algorithm by making use of the correlation between layers of the sum pyramid for a block. To speed our method, an algorithm is also developed to predict the initial motion vector for a template block. U
Autor:
Jim Z. C. Lai, Yi-Ching Liaw
Publikováno v:
Pattern Recognition. 41:3677-3681
In this paper, we present a modified filtering algorithm (MFA) by making use of center variations to speed up clustering process. Our method first divides clusters into static and active groups. We use the information of cluster displacements to reje
Publikováno v:
Pattern Recognition. 41:2956-2963
In this paper, we present a fast codebook re-quantization algorithm (FCRA) using codewords of a codebook being re-quantized as the training vectors to generate the re-quantized codebook. Our method is different from the available approach, which uses
Publikováno v:
Pattern Recognition. 41:315-319
In this paper, we present a fast codebook generation algorithm called CGAUCD (Codebook Generation Algorithm Using Codeword Displacement) by making use of the codeword displacement between successive partition processes. By implementing a fast search
Autor:
Jim Z. C. Lai, Yi-Ching Liaw
Publikováno v:
IEEE Signal Processing Letters. 14:117-120
The compression efficiency of an indexed image depends on the palette ordering. However, obtaining an optimal palette ordering is not an easy task, and approximate solutions are usually sought in practice. Among the available methods, the pairwise me