基于定向梯度特征直方图和极限学习机的蛇果分类

Rismiyati, H. A. Wibawa
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引用次数: 4

摘要

蛇果,或最著名的Salak,是印尼当地的水果。Salak也是来自印度尼西亚的水果商品之一。要在Salak上执行导出,需要执行严格的排序。排序通常是手动完成的。本研究将运用数位影像处理技术来区分沙拉品质,以供出口之用。Salak样品取自最大的Salak产地之一马格朗地区。本研究中使用的特征是定向梯度直方图。使用的分类是极限学习机(ELM)。本研究表明,使用ELM可以达到95%的最高准确率。本研究还使用了比较分类器SVM。在这种情况下,SVM能够达到97.3%的最高准确率,仍然高于ELM的结果
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Snake Fruit Classification by Using Histogram of Oriented Gradient Feature and Extreme Learning Machine
Snake fruit, or most famous as Salak, is Indonesian local fruit. Salak is also one of fruit commodity from Indonesia. To perform export on Salak, rigid sortation is performed. The sortation is usually done manually. This study will implement digital image processing technique to differentiate Salak quality for export purpose. Salak sample were taken from Magelang district, one of the largest Salak producer. The feature used in this study is Histogram of Oriented Gradient. The classification used is Extreme Learning Machine (ELM). It is shown in this study that by using ELM, the highest accuracy can be achieved is 95%. A comparison classifier, SVM, is also used in this study. In this case SVM is able to achieve highest accuracy of 97.3%, which is still higher than ELM result
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