An approach based on simulated annealing to optimize the performance of extraction of the flower region using mean-shift segmentation
A novel performance optimization approach (i.e. SAMS) for flower extraction using mean-shift segmentation (MS) is proposed. Simulated annealing solution of quadratic assignment problem (QAP) model is treated as an image segmentation process. The performance of Backprojection-based MS (BackMS) is improved by using simulated annealing-based MS (SAMS). For benchmark and segmentation, the object extractor using SAMS (OE-SAMS) software is introduced. The conclusion is based on the performance metrics and statistical analysis (i.e., Wilcoxon signed rank median test).
simulated annealing mean-shift segmentation performance optimization flower extraction quadratic assignment problem