西安电子科技大学学报

• 研究论文 • 上一篇    

目标尺寸先验与图像抽象的显著性检测

魏蕊1,2;何明一2;廉保旺2;周军妮1   

  1. (1. 西安建筑科技大学 信息与控制工程学院,陕西 西安 710055;
    2. 西北工业大学 电子信息学院,陕西 西安 710072)
  • 收稿日期:2016-08-01 出版日期:2017-02-20 发布日期:2017-04-01
  • 作者简介:魏蕊(1981-), 男, 助教,西北工业大学博士研究生,E-mail:weirui81@icloud.com
  • 基金资助:

    国家自然科学基金资助项目(61420106007)

Saliency detection via object size distribution prior and image abstraction

WEI Rui1,2;HE Mingyi2;LIAN Baowang2;ZHOU Junni1   

  1. (1. School of Information and Control Engineering, Xi'an Univ. of Architecture and Technology, Xi'an 710055, China;
    2. School of Electronics and Information, Northwestern Polytechnical Univ., Xi'an 710072, China)
  • Received:2016-08-01 Online:2017-02-20 Published:2017-04-01

摘要:

为了均匀突出显著目标并抑制小尺寸颜色独特的非显著目标对显著性检测的影响,研究了显著目标尺寸分布规律和多尺寸超像素抽象显著目标一致性,进而提出了基于目标尺寸先验的多尺寸超像素抽象显著性检测方法.该方法针对不同超像素尺寸抽象图计算图像的颜色独特性和颜色分布性,从局部和全局搜寻场景中的显著目标,并以尺寸分布规律指导显著目标的分割提取.通过对大量公开数据集中的图像进行测试的结果表明,该方法在有效检测显著目标的同时还能抑制小尺寸高对比度的非显著目标对显著性检测的影响,并生成均匀的高亮显著图.

关键词: 显著性检测, 图像抽象, 目标尺寸分布先验, 显著图

Abstract:

In order to uniformly highlight the entire salient object and reduce the influence of high contrast small-size objects on saliency detection, salient object size distribution regularity and consistency of salient objects in different scales image abstraction are investigated. A multi-scale abstraction saliency detection approach based on the object size distribution prior is proposed. The method measures the color uniqueness and distribution for different super-pixel abstraction images, and guides salient object segmentation and abstraction by the object size distribution regularity. Experimental results on publicly available image databases show that the method can accurately detect salient objects. Meanwhile, it can restrain the influence of small-size high contrast objects on saliency detection and generate a uniform saliency map.

Key words: saliency detection, image abstraction, object size distribution prior, saliency map