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计算机工程 ›› 2012, Vol. 38 ›› Issue (7): 148-151,154. doi: 10.3969/j.issn.1000-3428.2012.07.049

• 人工智能及识别技术 • 上一篇    下一篇

基于对数Gabor的超复数视觉显著性检测算法

李 策1,2,3,虎亚玲1,3, 曹 洁1, 田丽华2   

  1. (1. 兰州理工大学电气工程与信息工程学院,兰州 2. 西安交通大学人工智能与机器人研究所,西安 710049; 3. 甘肃省工业过程先进控制重点实验室,兰州 730050)
  • 收稿日期:2011-11-21 出版日期:2012-04-05 发布日期:2012-04-05
  • 作者简介:李 策(1974-),男,副教授、硕士,主研方向:计算机视觉,模式识别;虎亚玲,硕士研究生;曹 洁,教授;田丽华,讲师
  • 基金资助:
    甘肃省自然科学基金资助项目(1014ZSB064);中央高校基本科研业务费专项基金资助项目(XJJ20100062)

Hypercomplex Visual Saliency Detection Algorithm Based on Log-Gabor

LI Ce 1,2,3, HU Ya-ling 1,3, CAO 1, TIAN Li-hua 2   

  1. (1. College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China; 2. Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi’an 710049, China; 3. Key Laboratory of Advanced Control for Industrial Processes of Gansu Province, Lanzhou 730050, China)
  • Received:2011-11-21 Online:2012-04-05 Published:2012-04-05

摘要: 为在没有先验知识的情况下准确获取图像显著性目标,提出一种基于对数Gabor滤波器和超复数傅里叶变换的视觉显著性检测算法。利用对数Gabor滤波器模仿人类视觉感受野,对输入图像进行预处理,提取颜色、纹理方向等特征。根据所得特征构造各尺度下的超复数图像,并求其傅里叶变换相位谱,将多尺度超复数相位谱反变换后进行归一化,从而获得视觉显著图。实验结果表明,该算法与传统的算法相比具有更高的准确率,应用于复杂场景下的交通标志检测能取得较好的检测效果。

关键词: 视觉显著性, 对数Gabor, 超复数, 傅里叶变换, 多尺度, 显著图

Abstract: In order to obtain more accurate salient object from an image in the absence of priori knowledge, this paper proposes a visual saliency detection algorithm based on Log-Gabor filter and hypercomplex Fourier transform. It uses Log-Gabor filter to process input image and obtain color and texture feature, constructs a hypercomplex image using feature images, and calculates its Fourier transform phase spectral. It calculates visual saliency map by normalization. Experimental results show that the proposed method outperforms state-of-the-art methods remarkably in visual saliency and has better detection results in traffic sign detection.

Key words: visual saliency, Log-Gabor, hypercomplex, Fourier transform, multi-scale, saliency map

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