计算机科学 ›› 2014, Vol. 41 ›› Issue (12): 216-219.doi: 10.11896/j.issn.1002-137X.2014.12.047
段大高,龚乐,万月亮,韩忠明
DUAN Da-gao,GONG Le,WAN Yue-liang and HAN Zhong-ming
摘要: 昆虫翅脉提取对于昆虫自动分类意义重大。鉴于传统翅脉提取算法中存在断裂、边缘不整齐等缺点,提出一种基于张量投票的昆虫翅脉提取算法。首先对翅脉图像进行去噪、二值化、形态学等预处理,得到稀疏二值点图,然后计算每点的张量值,结合Gestalt定律的邻近性、相似性规则,对邻域内点进行张量投票,并设定投票阈值,最终获取昆虫翅脉轮廓。实验结果表明,由于引入张量和Gestalt规则,文中所提算法可以提取出更加符合感知规则的翅脉结构,得到较为完整且平滑的翅脉轮廓,同时对于出现少许断裂的翅脉图像,依然可以获得较为完整的翅脉边缘,这为后期的昆虫自动分类奠定基础。
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