An improved image segmentation algorithm based on the watershed transform

The watershed transform has a good response to the weak edge, but it is unable to obtain meaningful segmentation results directly by using the watershed transform to the phenomenon of excessive segmentation in image segmentation. A new segmentation algorithm base on improved watershed algorithm is proposed in this paper. By the different marks on the foreground and background objects, we can obtain better effect of segmentation with the application of watershed algorithm. Through the study of the characteristics of gradient image and morphological open close function reconstruction operations in image processing, a new tag extraction method will be designed by the new algorithm, which is by using the method of opening and closing by reconstruction operators to obtain marks and by controlling the closed reconstruction of structural elements in order to interested in the gradient image area the size of the tag. Then, extracted tag using morphological minimum calibration technology forces as an original local minimum value of the gradient image, and shields the original all local minimum value in the gradient image. In the end, watershed which is modified by the gradient of the image will have a image segmentation, in such aspects as outline eliminate over-segmentation and regional positioning have a very good segmentation effect.