A new implementation for the binary and Minkowski operators

Recursive binary dilation and erosion using digital line structuring elements in arbitrary orientations

Performing morphological operations such as dilation and erosion of binary images, using very long line structuring elements is computationally expensive when performed brute-force following definitions. We present two-pass algorithms that run at constant time for obtaining binary dilations and erosions with all possible length line structuring elements, simultaneously. The algorithms run at constant time for any orientation of the line structuring element. Another contribution of this paper is the use of the concept of orientation error between a continuous line and its discrete counterpart. The orientation error is used in determining the minimum length of the basic digital line structuring element used in obtaining what we call dilation and erosion transforms. The transforms are then thresholded by the length of the desired structuring element to obtain the dilation and erosion results. The algorithms require only one maximum operation for erosion transform and only one minimum operation for dilation transform, and one thresholding step and one translation step per result pixel. We tested the algorithms on Sun Sparc Station 10, on a set of 240x250 salt and pepper noise images with probability of a pixel being a 1-pixel set to 0.25, for orientations of the normals of the structuring elements in the range [pi/2,3pi/2] and lengths, in pixels, in the range [5,145]. We achieved a speed up of about 50 (and for special orientations theta in {(pi/2), (3pi/4), pi, (5pi/4), (3pi/2)} a speed up of about 100) when the structuring elements had lengths of 145 pixels, over the brute-force methods in these experiments. We compared the results of our dilation algorithm with those of the algorithm discussed by Soille et al. (see IEEE Trans. Pattern Anal. Machine Intell., vol.18, p.562-67, 1996) and showed that for binary dilation (and erosion since it is just the dilation of the background with the reflected structuring element) our algorithm performed better and achieved a speed up of about four when dilation or erosion transform alone is obtained.

Recognition of organs in CT-image sequences: a model guided approach

A method is proposed for segmentation of organs in CT-image sequences. An important feature of the method is the use of search areas to guide the segmentation process. Time consuming, data-directed operations are restricted to these areas, instead of being applied to the whole image. A search area for a particular anatomical structure is determined by constraints, derived from a model of the imaged scene and by results already obtained in the recognition process. The method has been successfully applied on recognition of the spleen in abdominal X-ray CT scans.

Characterization of chromatin distribution in cell nuclei

In this paper we develop four measures to describe the distribution of nuclear chromatin. These measures attempt to describe in an objective and meaningful way the heterogeneity, granularity, condensation, and margination of chromatin in cell nuclei. Starting with a high-resolution digitized image of a cell where the nuclear pixels have been identified, the four measures may be rapidly estimated. The range of each is derived and the interpretation of the measures in the context of chromatin compaction and distribution is developed. Implementation issues such as sampling density, thresholding and subsequent pre-processing, and algorithmic complexity are discussed.