关键词: 自适应, 显著性检测, 贝叶斯理论, 阈值算法, 滑动窗口

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.

Key words: adaptive, saliency detection, Bayesian theory, threshold algorithm, sliding window