Shape-based sorting of agricultural produce using support vector machines in a MATLAB / SIMULINK environment

Min Min Kyaw, Syed Khaleel Ahmed, Z. Sharrif
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引用次数: 15

Abstract

The ability to sort agricultural produce automatically is very important. This paper addresses one way to identify agricultural produce based on their shape. The techniques used are based on support vector machines. The images of the produce are loaded into MATLAB and the features extracted using image processing techniques based on edge detection. These features are then input to a classifier; i.e., a support vector machine, for identification. A regular digital camera is used for acquiring the image, and all manipulations are performed in a MATLAB / SIMULINK environment. The results obtained are an improvement over a previous technique.
在MATLAB / SIMULINK环境下使用支持向量机进行农产品形状分选
农产品自动分拣的能力是非常重要的。本文提出了一种基于农产品形状来识别农产品的方法。所使用的技术是基于支持向量机。将农产品图像加载到MATLAB中,利用基于边缘检测的图像处理技术提取特征。然后将这些特征输入到分类器中;即,用于识别的支持向量机。图像采集采用普通数码相机,所有操作均在MATLAB / SIMULINK环境下完成。所获得的结果比以前的技术有了改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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