Open AccessMeta-heuristic Optimization Algorithms for Irradiated Fruits and Vegetable Image Detection
Author(s) -
Wessam S. Elaraby,
Ahmed H. Madian
Publication year - 2022
Publication title -
wseas transactions on computers
Language(s) - English
Resource type - Journals
eISSN - 2224-2872
pISSN - 1109-2750
DOI - 10.37394/23205.2022.21.17
Subject(s) - cuckoo search , food irradiation , algorithm , computer science , irradiation , artificial intelligence , histogram , metaheuristic , optimization algorithm , particle swarm optimization , mathematics , mathematical optimization , image (mathematics) , physics , nuclear physics
Despite the food irradiation benefits, it isn’t accepted. Food irradiation is the process that exposed foodi to ionizationi radiation, suchi as electroni beams, X-raysi, or gammai radiationi to inactivate food spoilage organisms. This paper discusses the effect of radiation on the food images, how the food changes before and after taking the radiation dose, and how the PSNR (Peak Signal to Noise Ratio) changes using different metaheuristic optimization algorithms. In this paper, Image Segmentation is based on three different metaheuristic algorithms used to detect the difference between before and after irradiation. The three algorithms are (1) PSOi (Particle Swarmi Optimization), DPSOi (Darwiniani PSO), andi FO-DPSOi (Fractional-Orderi DPSOi), (2) CS (Cuckoo Search), and (3) SFLA (Shuffled Frog Leaping Algorithm). The algorithms succeeded in discovering the effect of radiation on Green Apple, Cucumber, and Orange even if it is not visually recognized. Also, the histogram of the image shows the difference between before and after irradiation.