This paper suggests an improved marker-based watershed image-segmentation method to reduce the over-segmentation of the watershed algorithm. The new method applies the watershed transform directly on the original gradients image instead of simplified image

so that the loss of boundary information can be avoided. On the other hand

we design a new marker-extracted approach to extract the regional minima related to the objects from the low frequency components of the gradients. These extracted minima constitute the binary marker image. And then the extracted markers are imposed on the original gradients as its minima

while all its intrinsic minima are suppressed. Finally

the watershed algorithm is applied to the modified gradients by the markers to reduce effectively the over-segmentation. Across a variety of image types

it is proven that this new method can obtain meaningful and homogeneous regions with accurate

consecutive and one-pixel wide boundary. Compared with other methods

this system requires fewer computations and simpler parameters and can more efficiently reduce the over-segmentation of the watershed algorithm.