The International Journal of Multimedia & Its Applications (IJMA) Vol.4, No.3, June 2012 DOI : 10.5121/ijma.2012.4301 1           Ahmad EL ALLAOUI 1 and M’barek NASRI 1 1 LABO MATSI, ESTO, B.P 473, University Mohammed I OUJDA, MOROCCO. ahmadallaoui@yahoo.fr ; nasri@est.ump.ma ABSTRACT Segmentation by watershed transform is a fast, robust and widely used in image processing and analysis, but it suffers from over-segmentation. We present in this paper some improvements to this algorithm based on the mathematical morphology in order to get over this difficulty. The performance of this method is validated on medical images. The results obtained show the good performance of this approach. KEYWORDS Image processing, medical image segmentation, watershed, Marker controlled watershed, reconstruction, dilatation, Mathematical morphology. 1. INTRODUCTION The segmentation is a very important stage in images and interpretation processing. There are two main approaches to segmentation: the frontier approach and the region approach [13, 14]. The segmentation by watershed combine the two approaches [1, 2].This is a powerful technique for rapid detection of both edges and regions. The major problem of the watershed transform is over-segmentation. Indeed, this algorithm is sensitive to any local minimum in the image, and tends to define the lines of the watershed transform where each local minimum gives rise to a region. To avoid this problem, powerful tools adapted to different problems have been proposed in the literature [3, 7]:  Either reduce the number of minima and avoid calculation of too many regions.  Proceed by either filtering techniques by merging the regions according to similarity criteria after spectral and spatial application of the watershed. We have used markers to reduce the number of regional minima. In Section 2 image segmentation with watershed algorithm is presented. The proposed method is presented in section 3. In section 4, a validation of our approach is given; experimental results are obtained by medical images. Finally we give a conclusion.