Contour pocketing computation using mathematical morphology

Character Recognition Using Mathematical Morphology

We describe our partially completed work on a set of morphological algorithms for recognizing handwritten numerals. The basic morphological operations { dilation, erosion, opening and closing { are used to extract characteristic features of these characters and check for their appropriate topological con guration. The paper describes the key shape characterization for two groups containing a to...

Imagemap simplification using mathematical morphology

For a variety of mapping applications, images are the most important primary data sources. In photogrammetry and remote sensing, particular procedures are used for image and map data integration in order to perform change detection and automatic object extraction. The recognition of an object in an image is a complex task that involves a broad range of techniques. In general, three steps are us...

Computation of contour integrals

Greyscale Image Interpolation Using Mathematical Morphology

When magnifying a bitmapped image, we want to increase the number of pixels it covers, allowing for finer details in the image, which are not visible in the original image. Simple interpolation techniques are not suitable because they introduce jagged edges, also called “jaggies”. Earlier we proposed the “mmint” magnification method (for integer scaling factors), which avoids jaggies. It is bas...

Granulometry Using Mathematical Morphology and Motion

This paper describes an efficient framework for image-based granulometry, which provides three main contributions. First, unlike most of the existing work on particle delineation, which is based on the use of detected edges, our method-a regionbased approach-relies on the use of mathematical morphology techniques. Second, we have explored the use of motion in order to recover the visible volume...