Bio-Inspired-Fossil-Image-Segmentation-for-Paleontology

%%************************************************************************ %% Bio-Inspired Fossil Image Segmentation for Paleontology %% Developed by Seyed Muhammad Hossein Mousavi between Jan to July of 2022. % This code could be used as a tool for paleontologist. % This is demo version of: %------------------------------------------------------------------------ %% Mousavi, S. M. H. (2022). Bio-Inspired Fossil Image Segmentation for %% Paleontology. International Journal of Mechatronics, Electrical and %% Computer Technology (IJMEC), 12(45), 5243-5249. %------------------------------------------------------------------------ % So, please cite after use. % Paper link: % https://www.aeuso.org/includes/files/articles/Vol12_Iss45_5243-5249_Bio-Inspired_Fossil_Image_Segmentat.pdf %% The code is consisted of following steps: % 1.Evolution Strategy (ES) Histogram Equalization % Histogram equalization is a method in image processing of % contrast adjustment using the image's histogram % 2.Cultural Algorithm (CA) Image Quantization % Quantization, involved in image processing, is a lossy compression technique % achieved by compressing a range of values to a single quantum value. % When the number of discrete symbols in a given stream is reduced, the % stream becomes more compressible. % 3.Simulated Annealing (SA) Edge Detection % Edge detection is used to identify points % in a digital image with discontinuities, simply to say, sharp changes in % the image brightness. % 4.Particle Swarm Optimization (PSO) Image Segmentation % Image segmentation is the process of partitioning a digital image into % multiple image segments, also known as image regions or image objects % 5.Final Overlay % F-Score performance metric evaluates the system VS ground truth % Hope this code could help you. Let's dive in => %%======================================================================