Surface Characterization of a Paper Web at the Wet End

We present an algorithm for the detection and representation of structures and non-uniformities on the surface of a paper web at the wet end (slurry). This image processing/analysis algorithm is developed as part of a complete on-line web characterization system. Images of the slurry, carried by a fast moving table, are obtained using a stroboscopic light and a CCD camera. The images have very poor contrast and contain noise from a variety of sources. Those sources include the acquisition system itself, the lighting, the vibrations of the moving table being imaged, and the scattering water from the same table's movement. After many steps of enhancement, conventional edge detection methods were still inconclusive and were discarded. The facet model algorithm, is applied to the images and is found successful in detecting the various topographic characteristics of the surface of the slurry. Pertinent topographic elements are retained and a filtered image is computed based on the general appearance and characteristics of the structures in question. Morphological operators are applied to detect and segment regions of interest. Those regions are then filtered according to their size, elongation, and orientation.Their bounding rectangles are computed and superimposed on the original image. Real time implementation of this algorithm for on-line use is also addressed in this paper. The algorithm is tested on over 500 images of slurry and is found to detect nonuniformities on all 500 images. Locating and characterizing all different size structures is also achieved on all 500 images of the web