Novel Algorithm for Threshold Selection in Pattern Recognition Applications


Authors : Rahul Soni , Anupam Agarwal.

Volume/Issue : Volume 2 - 2017, Issue 6 - June

Google Scholar : https://goo.gl/DaAS3K

Scribd : https://goo.gl/QsMLpL

Thomson Reuters ResearcherID : https://goo.gl/3bkzwv

In this article, threshold selection is done on the basis of different entropy measures on both gray scale and color images. Comparative study of the Shannon and non-Shannon entropies (Renyi, Havrda Charvat, Kapur and Vajda) is done to obtain an appropriate threshold value for the purpose of image segmentation. It is observed through the simulation experiments performed on images, that the position of the smallest minima obtained in the entropy versus gray-level plot is different for each entropy measure. The threshold values obtained from these plots is therefore dependent on the particular definition of the entropy chosen, which in turn affects the segmentation results. Quantitative evaluation of the quality of the enhanced images is also an important issue. Several measures have been proposed in the literature for this purpose [23]. In this article, we propose and investigate the use of different entropy measures for quantitative evaluation of the quality of enhanced images. Simulation results of quantitative evaluation of the quality of the enhanced images using different entropy measures are also presented.

Keywords : image segmentation,thresholding.

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