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蒋林华, 钟荟, 林晓, 马利庄. 基于自适应遗传算法的显著性检测[J]. 计算机辅助设计与图形学学报, 2017, 29(11): 1971-1979.
引用本文: 蒋林华, 钟荟, 林晓, 马利庄. 基于自适应遗传算法的显著性检测[J]. 计算机辅助设计与图形学学报, 2017, 29(11): 1971-1979.
Jiang Linhua, Zhong Hui, Lin Xiao, Ma Lizhuang. Adaptive Genetic Algorithm on Saliency Detection[J]. Journal of Computer-Aided Design & Computer Graphics, 2017, 29(11): 1971-1979.
Citation: Jiang Linhua, Zhong Hui, Lin Xiao, Ma Lizhuang. Adaptive Genetic Algorithm on Saliency Detection[J]. Journal of Computer-Aided Design & Computer Graphics, 2017, 29(11): 1971-1979.

基于自适应遗传算法的显著性检测

Adaptive Genetic Algorithm on Saliency Detection

  • 摘要: 为了更鲁棒地检测图像中的显著目标.在凸包的基础上,提出一种基于自适应遗传算法的显著性检测算法.首先通过图像的Harris角点构造凸包,利用自适应遗传算法来找出凸包内的显著目标并构造遗传先验图;然后构建中心先验模型,与遗传先验图融合成先验图;最后引入贝叶斯优化框架来优化先验图,以得到最终的显著图.在6个公开的显著性检测数据库上进行评测,通过大量实验验证了该算法的有效性.

     

    Abstract: In order to more robustly detect the salient targets in images,based on the convex hull,our paper proposed a saliency detection algorithm based on adaptive genetic algorithm.Firstly,the convex hull is constructed by Harris points of the image,the adaptive genetic algorithm is used to find the salient areas of convex hull and construct the genetic prior map.Then,construct center prior model and integrate genetic prior map and center prior model into a prior map; use Bayesian optimization framework to optimize the prior map to obtain the final saliency map.Our algorithm is evaluated on the six open saliency dataset.Extensive experimental results demonstrate that our algorithm is effective.

     

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