Affiliations: Machine Intelligence Unit, Indian Statistical
Institute, Kolkata, India. E-mail:{pmaji,malay}@isical.ac.in | Electronics and Communication Sciences Unit, Indian
Statistical Institute, Kolkata, India. E-mail:chanda@isical.ac.in
Note: [] Address for correspondence: Machine Intelligence Unit, Indian
Statistical Institute, 203 B. T. Road, Kolkata, 700 108, India
Abstract: A robust thresholding technique is proposed in this paper for
segmentation of brain MR images. It is based on the fuzzy thresholding
techniques. Its aim is to threshold the gray level histogram of brain MR images
by splitting the image histogram into multiple crisp subsets. The histogram of
the given image is thresholded according to the similarity between gray levels.
The similarity is assessed through a second order fuzzy measure such as fuzzy
correlation, fuzzy entropy, and index of fuzziness. To calculate the second
order fuzzy measure, a weighted co-occurrence matrix is presented, which
extracts the local information more accurately. Two quantitative indices are
introduced to determine the multiple thresholds of the given histogram. The
effectiveness of the proposed algorithm, along with a comparisonwith standard
thresholding techniques, is demonstrated on a set of brain MR images.
Keywords: Medical imaging, segmentation, thresholding, fuzzy sets, co-occurrence matrix
