Herb flower recognition system (HFRS)

C. Pornpanomchai, Ponrath Sakunreraratsame, Rosita Wongsasirinart, Nuttakan Youngtavichavhart
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引用次数: 10

Abstract

The objective of this research is to build an automatic method for recognizing a Thai herb flower based on the Minimum Distance Method. The herb flower images, acquired from a digital camera, are taken in the real environment. We use the characteristics of herb flowers to design our classification algorithms, which consist of the average red, green and blue (RGB) colors, the herb flower size and the edge of petals feature. The experiments are conducted on more than 380 pictures from 16 species of herb flowers. The training data set is around 220 pictures. We test the system by using 110 pictures for a training data set and 50 pictures for an un-training data set. The precision rates of the recognition system are 98.18 percent and 94 percent, respectively. The average access time is 0.87 seconds per image.
草本花卉识别系统(HFRS)
本研究的目的是建立一种基于最小距离方法的泰国草本花卉自动识别方法。从数码相机获取的草本花卉图像是在真实环境中拍摄的。我们利用草本花的特征来设计我们的分类算法,该算法由平均红、绿、蓝(RGB)颜色、草本花的大小和花瓣边缘特征组成。实验是在16种草本花卉的380多张图片上进行的。训练数据集大约有220张图片。我们使用110张图片作为训练数据集,50张图片作为非训练数据集来测试系统。该识别系统的准确率分别为98.18%和94%。每个映像的平均访问时间为0.87秒。
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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