On-Line Signature Verification With Two-Stage Statistical Models
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
A Neuro Fuzzy Model for Image Compression in Wavelet Domain
ICISP '08 Proceedings of the 3rd international conference on Image and Signal Processing
Adaptive terrain-based memetic algorithms
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
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Previously a modified K-means algorithm for vector quantization design has been proposed where the codevector updating step is as follows: new codevector=current codevector+scale factor (new centroid-current codevector). This algorithm uses a fixed value for the scale factor. In this paper, we propose the use of a variable scale factor which is a function of the iteration number. For the vector quantization of image data, we show that it offers faster convergence than the modified K-means algorithm with a fixed scale factor, without affecting the optimality of the codebook