A fourth note on recent research in geometrical probability

Recent research on topics related to geometrical probability is reviewed. The survey includes articles on random points, lines, line-segments and flats in Euclidean spaces, the random division of space, coverage, packing, random sets, stereology and probabilistic aspects of integral geometry.

Parallel processing in machine vision

Machine vision systems incorporating highly parallel processor architectures are reviewed. A new processor architecture, the image flow computer, is presented in detail. An interactive image processing programming language based on mathematical morphology is then presented. A detailed example of the use of the system for the inspection of a particular industrial part concludes the presentation.

Pipeline architectures for recursive morphological operations

Introduces efficient pipeline architectures for the recursive morphological operations. The standard morphological operation is applied directly on the original input image and produces an output image. The order of image scanning in which the operator is applied to the input pixels is irrelevant. However, the intent of the recursive morphological operations is to feed back the output at the current scanning pixel to overwrite its corresponding input pixel to be considered into computation at the following scanning pixels. The resultant output image by recursive morphology inherently depends on the image scanning sequence. Two pipelined implementations of the recursive morphological operations are presented. The design of an application-specific systolic array is first introduced. The systolic array uses 3 n cells to process an nxn image in 6 n-2 cycles. The cell utilization rate is 100%. Second, a parallel program implementing the recursive morphological operations and running on distributed-memory multicomputers is described. Performance of the program can be finely tuned by choosing appropriate partition parameters.

A fast thresholded linear convolution representation of morphological operations

In this correspondence, we present a fast thresholded linear convolution representation of morphological operations. The thresholded linear convolution representation of dilation and erosion is first proposed. A comparison of the efficiency of the direct implementation of morphological operations and the thresholded linear convolution representation of morphological operations is subsequently conducted. Mathematical morphology has emerged as a powerful new tool for image processing.

Evaluation of the reorganization in the high-order structure of DNA occurring during cell senescence

Electron microscopic pictures of loosened chromatin obtained from human fibroblasts aged in vitro were analyzed with an image processor. It was found that the density of the 30-nm chromatin fibers decreased progressively through the cell population lifespan. The spacing between the fibers increased abruptly during the last divisions (phase IV). The evolution of these 2 parameters, density and spacing, was identical, respectively, with that of the decline in the rate of initiating DNA synthesis after seeding the cells and with that of the maximal percent of cells synthesizing DNA during a 24-h period between seeding and resting phase. Cells from 2 human donors (30 and 60 years old) with Werner's syndrome were compared, using the same methodology, with those of 9 normal donors ranging from 29 to 98 years old. The spacing between chromatin fibers in the Werner's cells was significantly increased as compared to the age-matched normal controls while the density was within the normal range. The results are discussed with regard to other modifications in DNA structure previously reported in the same cell system.

Image analysis using mathematical morphology

For the purposes of object or defect identification required in industrial vision applications, the operations of mathematical morphology are more useful than the convolution operations employed in signal processing because the morphological operators relate directly to shape. The tutorial provided in this paper reviews both binary morphology and gray scale morphology, covering the operations of dilation, erosion, opening, and closing and their relations. Examples are given for each morphological concept and explanations are given for many of their interrelationships.