Abstract:
Image segmentation is concerned with decomposing a given image into its constituent regions or objects. It is an important preliminary step in diverse fields of application like object recognition, image compression, medical image processing and biological analysis methods. Among the existing segmentation algorithm, watershed transformation is deemed to be a powerful tool for image segmentation owing to the simplicity of its formulation and implementation and its ability to identify the important closed contours of a given image. However, the time complexity of the majority of the watershed transform algorithms is quite high making their real- time application difficult. In particular, real time processes like moving object segmentation, road traffic monitoring and analysis of steel fracture demand fast computation of watershed transformation for image segmentation. At the same time a dedicated hardware architecture for implementing watershed algorithms would give rise to faster results as compared to a software program executed on a general purpose processor.
