Battle Royale Optimization Algorithm for Automatic Threshold Selection in Cervical Pap Smear Images

Selecting the accurate threshold in image plays a significant role in image segmentation. The various threshold techniques which were proposed by the researchers are not effective in terms of automatic threshold selection. This paper introduces the Battle Royale Optimization (BRO) algorithm to image segmentation for the automatic threshold selection. The proposed work searches optimal threshold value for segmentation by using BRO. The pap smear slide samples were used for simulation experiments whereas the obtained results evaluated using Peak to Signal Noise Ratio (PSNR), Jaccard Index (JI), and Dice Coefficient (DC). The results obtained from the proposed work shows better performance significantly in addressing the issue of large computation and low efficiency.