摘要
结合对象估计和超像素分割,提出面向多目标的显著性区域提取算法.首先,应用对象估计对图像中的多目标作初步检测,得到若干个显著性区域的初步结果;然后,再将这些显著性区域与超像素分割的结果作图像拼接,完善这些显著性区域;最后,将图像拼接的结果二值化,作为多目标显著性区域提取的最终结果.结果表明:所提算法可实现面向多目标的显著性区域提取.与3个经典算法的比较结果表明:所提算法在面向多目标显著性区域提取时更优.
Combining object estimation and super-pixel segmentation,a salient region extraction algorithm for multi-target was proposed.First,object estimation was used to make a preliminary extraction of multi-target in image,and the preliminary results of several salient regions were obtained.Then,these several salient regions were concatenated with the results of super-pixel segmentation to complete the saliency extraction.Finally,the concatenated regions were binarized as the final results of salient region for multi-target.The results showed that the proposed algorithm can achieve multi-target salient region extraction.The comparison with three classical algorithms indicated that the proposed algorithm is better when it is faced with salient region extraction for multi-target.
作者
孟琭
陈妹雅
MENG Lu;CHEN Mei-ya(School of Information Science&Engineering,Northeastern University,Shenyang 110819,China)
出处
《东北大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2018年第10期1380-1384,共5页
Journal of Northeastern University(Natural Science)
基金
国家自然科学基金资助项目(61101057)
关键词
多目标
显著性区域
对象估计
超像素分割
图像处理
multi-target
salient region
object estimation
super-pixel segmentation
image processing
