Slant correction is a preprocessing technique to improve segmentation and recognition accuracy for handwritten word recognition. All conventional slant correction techniques were performed by the estimation of the average slant angle and the shear transformation. In this paper, a nonuniform slant correction technique for handwritten word recognition is proposed where the slant correction problem is formulated as a global optimal estimation problem of the sequence of local slant angles. The optimal estimation is performed by a dynamic programming based algorithm. From experimental results it was shown that the present technique outperforms conventional uniform slant correction techniques.