Multilevel thresholding image segmentation based on energy curve with harmony Search Algorithm

Abstract

Image segmentation is a process of portion image into regions. From image segmentation schemes available, multilevel thresholding on the histogram is a highly established method. Otsu’s method is a significant multilevel thresholding technique, in this multiple threshold levels selected on histogram and group the pixels of an image into different regions. The optimized threshold levels computed with an Optimized technique by maximizing the inter-class variance. Methods with histograms are incapable to possess spatial details of contextual information for finding optimal threshold levels. As a remedy, a novel method proposed the Energy Curve is used instead of a histogram with Otsu’s method and Harmony Search Algorithm to compute optimized gray levels. The proposed method experimented on several benchmark images, and results compared with various optimization algorithms with histogram by Dunn Index, DB Index, SD Index, mean of fitness and PSNR, comparison clarifies that the proposed method is superior to histogram-based methods.

Keywords

• Image segmentation
• Otsu method
• Multilevel thresholding
• Energy curve
• Harmony search algorithm