摘要
针对目前翘板黑瓜子依赖手工检测效率低下的问题,提出了一种利用光度立体视觉算法进行翘板瓜子识别的方法。首先利用实物表面重建的方法标定了图像采集系统的精度;然后针对黑瓜子表面中间区域与周边区域颜色有巨大差异的特殊形态,分区域三维重建了黑瓜子表面;最后通过试验确定表面面积为识别特征,识别阈值为9,在误识率小于5%的情况下,翘板瓜子识别率达90%。试验结果表明应用光度立体视觉算法可以有效地进行翘板黑瓜子的识别。
At present, the cleaning of wrinkled black melon seeds is performed manually, which has extremely low efficiency. As to the problem, a method for identifying wrinkled black melon seeds with photometric stereo is proposed in this paper. First, the accuracy of image capturing system was calibrated by constructing a testing entity surface. Then, as there was a great color difference between the central and the periphery area of the black melon seeds, the two parts of surfaces were separately reconstructed. Finally, experiments were done to determine transverse surface area as the identification feature, and the threshold is nine. It was shown that more than 90% of the wrinkled melon seeds could successfully be identified while the error rate is below 5%. From the experiments, it can be concluded that the algorithm of photometric stereo can be used to identify the wrinkled black melon seeds effectively.
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2007年第5期159-163,共5页
Transactions of the Chinese Society of Agricultural Engineering
基金
高等学校博士学科点专项科研基金(20050019005)
关键词
机器视觉
表面三维重建
光度立体法
翘板黑瓜子识别
machine vision three-dimensional surface reconstruction
photometric stereo identification of wrinkled black melon seeds
作者简介
李昊宇（1981-），男，山西大同人，研究方向：视觉检测。北京中国农业大学工学院，100083。Email：lihaoy1128@163．com
通讯作者：李伟，教授，博士生导师，主要研究领域为计算机视觉检测技术，农业自动化装备技术。北京市海淀区清华东路17号中国农业大学工学院，100083。Email：gxy5@cau．edu．cn
