计算机工程与应用2017，Vol.53Issue(13)：201-205,5.DOI:10.3778/j.issn.1002-8331.1601-0346
基于贝叶斯理论的自适应显著性检测
Adaptive saliency detection algorithm based on Bayesian theory
摘要
Abstract
Traditional saliency detection based on Bayesian theory usually uses the fixed window form and with poor adaptability. This paper presents an adaptive saliency detection algorithm based on Bayesian theory that can take the different picture with different salient objects into account. Firstly, picture edge is extracted by Canny algorithm, then an adaptive window is determined by threshold algorithm, finally the paper uses Bayesian algorithm to compute saliency map. The given adaptive window can fit better the salient objects. Experimental results show that the proposed method has higher precision and better recall compared with other traditional Bayesian algorithms and classical algorithm.关键词
自适应/显著性检测/贝叶斯理论/阈值算法/滑动窗口Key words
adaptive/saliency detection/Bayesian theory/threshold algorithm/sliding window分类
信息技术与安全科学引用本文复制引用
郭磊,王晓东,王刚,陈超..基于贝叶斯理论的自适应显著性检测[J].计算机工程与应用,2017,53(13):201-205,5.基金项目
国家科技支撑计划(No.2012BAH67F01) （No.2012BAH67F01）
国家自然科学基金(No.60832003,No.61071120) （No.60832003,No.61071120）
浙江省教育厅科研计划项目(No.Y201327703) （No.Y201327703）
宁波市科技创新团队研究计划(No.2011B81002) （No.2011B81002）
省科技厅/创新团队自主设计项目(No.2012R10009-08) （No.2012R10009-08）
浙江省自然科学基金(No.Y1110161). （No.Y1110161）
