基于模糊逻辑和支持向量机的农产品分类与分级

N.B.A. Mustafa, S. K. Ahmed, Z. Ali, W. B. Yit, A. Abidin, Z. Sharrif
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引用次数: 54

摘要

农业部门在第九大马计划(9MP)中获得了非常不同的待遇,该部门正在振兴,成为经济增长引擎的一部分。信息和通信技术(ICT)应用将作为改善农业部门地位的解决方案实施。将信息和通信技术与农业部门相结合的想法推动了农业产品分类和分级自动化系统的发展。目前,分级是根据观察和经验进行的。开发的系统通过使用普通数码相机或手机相机捕捉水果的图像来开始分级过程。然后将图像传输到处理层,利用MATLAB进行特征提取、分类和分级。本文主要对农产品分选分级技术进行了研究。利用支持向量机(svm)对农产品的形状和大小进行分类,并用模糊逻辑(FL)方法确定农产品的等级。所得结果是很有希望的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Agricultural produce Sorting and Grading using Support Vector Machines and Fuzzy Logic
Agriculture sector was accorded a very different treatment in the Ninth Malaysia Plan (9MP) where this sector is being revitalized to become a part of the economic growth engine. The Information and Communication Technology (ICT) application is going to be implemented as a solution in improving the status of the agriculture sector. The idea of integrating ICT with agriculture sector motivates the development of an automated system for sorting and grading of agriculture produce. Currently, the grading is done based on observations and through experience. The developed system starts the grading process by capturing the fruit's image using a regular digital camera or mobile phone camera. Then, the image is transmitted to the processing level where feature extraction, classification and grading is done using MATLAB. In this paper, the focus is more on agricultural produce Sorting and Grading technique. The agricultural produce is classified based on fruit shape and size using Support Vector Machines (SVMs) and its grade is determined using Fuzzy Logic (FL) approach. The results obtained are very promising.
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