Genome-wide nucleosome prediction has been an important research area in genetics so far. However, most existing nucleosome prediction algorithms are based on the statistical features of nucleosome-bound DNA sequences, usually resulting in low accuracies. Basides our statistical studies in linker DNA sequences, each of which connects with two nucleosome-bound DNA sequences, show that linker DNA sequences have some specific statistical properties.Concerning the fact, improvement of the Segal model is presented, where two score functions are constructed, based on the dinucleotide position frequencies of the nucleosome-bound and linker DNA sequences respectively. Nucleosome positions are predicted according to the difference between the above two score functions. Experimental results on the yeast’s chromatin demonstrate that the improved algorithm can significantly increase the accuracy in positioning nucleosomes.