Quantitative Characterization of Electron Micrograph Image Using Fractal Feature

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

51 Citations (Scopus)

Abstract

In this investigation, texture analysis was carried out on electron micrograph images. Fractal dimensions and spatial grey level co-occurrence matrices statistics were estimated on each homogeneous region of interest. The fractal model has the advantages that the fractal dimension correlates to the roughness of the surface and is stable over transformations of scale and linear transforms of intensity. It can be calculated using three different methods. The first method estimates fractal dimension based on the average intensity difference of pixel pairs. In the second method, fractal dimension is determined from the Fourier transformed domain. Finally, fractal dimension can be estimated using reticular cell counting approach. Moreover, automatic image segmentation was performed using fractal dimensions, spatial grey level co-occurrence matrices statistics, and grey level thresholding. Each image was segmented into a number of regions corresponding to distinctly different morphologies: heterochromatin, euchromatin, and background. Fractal dimensions and spatial grey level co-occurrence matrices statistics were found to be able to characterize and segment electron micrograph images. © 1995 IEEE
Original languageEnglish
Pages (from-to)1033-1037
JournalIEEE Transactions on Biomedical Engineering
Volume42
Issue number10
DOIs
Publication statusPublished - Oct 1995

Fingerprint

Dive into the research topics of 'Quantitative Characterization of Electron Micrograph Image Using Fractal Feature'. Together they form a unique fingerprint.

Cite this