摘要
综合利用计算机视觉、图像处理技术,增加茶叶的形状参数,改进神经网络算法,实现了茶叶品质识别的自动化。研究中通过数码相机等直接得到茶叶图像,经过对图像格式进行转换和预处理,然后基于HSI模型提取的茶叶颜色特征参数和二值化后图像提取的茶叶形状特征参数,通过遗传神经网络,最后完成对茶叶的自动识别。实验结果表明此方法能取得更好的识别效果,计算机的检测结果与人工检测结果高度吻合。
The figure characteristics of tea and improved neural-network, computer vision and image processing were combined together to realize automatic identification of external quality of tea leaf. Firstly a tea-leaf image was obtained by a digital camera directly. The parameters of tea HSI model and parameters of the figure was extracted to identify tea leaf after image conversion and preprocess. Then completed automatically identify of tea-leaf through the Genetical-Neural network. The experiments reveal that the method improves the consistence between computer inspection and manual inspection.
出处
《茶叶科学》
CAS
CSCD
北大核心
2008年第6期420-424,共5页
Journal of Tea Science
关键词
茶叶
颜色
形状
图像处理
遗传算法
神经网络
识别
tea, color, figure, image processing, genetical-arithmetic, neural-network, identification
作者简介
汪建（1968-），男，四川雅安人，副教授，主要从事计算机图像处理、模式识别方面的研究。
