辐照果蔬图像检测的元启发式优化算法

Wessam S. ElAraby, A. Madian
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引用次数: 0

摘要

尽管食品辐照有好处,但它并没有被接受。食品辐照是将食品暴露于电离辐射(如电子束、x射线或伽马射线)以灭活食品腐败生物体的过程。本文采用不同的元启发式优化算法,讨论了辐射对食品图像的影响,辐照前后食品图像的变化,以及峰值信噪比的变化。在本文中,图像分割基于三种不同的元启发式算法,用于检测辐照前后的差异。这三种算法分别是(1)PSOi (Particle Swarmi Optimization)、DPSOi (Darwiniani PSO)、andi FO-DPSOi(分数有序DPSOi)、(2)CS (Cuckoo Search)和(3)SFLA (Shuffled Frog leapalgorithm)。该算法成功地发现了辐射对绿苹果、黄瓜和橙子的影响,即使它不能被视觉识别。同时,图像的直方图显示了辐照前后的差异。
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Meta-heuristic Optimization Algorithms for Irradiated Fruits and Vegetable Image Detection
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.
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