上海交通大学学报(自然版) ›› 2012, Vol. 46 ›› Issue (09): 1421-1427.

• 自动化技术、计算机技术 • 上一篇    下一篇

海面目标自适应实时检测  

万磊,曾文静,秦再白,黄蜀玲   

  1. (哈尔滨工程大学 水下机器人技术国防科技重点实验室, 哈尔滨 150001)  
  • 收稿日期:2011-10-31 出版日期:2012-09-28 发布日期:2012-09-28
  • 基金资助:

    国家自然科学基金资助项目(51009040E091002), 国家高技术研究发展计划(863)项目资助(2011AA09A106)

Real-time Detection of Sea Surface Targets

 WAN  Lei, ZENG  Wen-Jing, QIN  Zai-Bai, HUANG  Shu-Ling   

  1. (State Key Laboratory of Autonomous Underwater Vehicle, Harbin Engineering University,
    Harbin 150001, China)
  • Received:2011-10-31 Online:2012-09-28 Published:2012-09-28

摘要: 针对海面运动载体所获得的可见光序列图像及图像自身特点,提出了一种既适应于海天背景下的小目标而又适应于海岸背景下的大目标的目标快速自动检测方法.首先,量化子图像的区域复杂度以及单元区域上、下邻域的灰度差异,以预测并定位海界限区域,摒弃不含海界限区域的图像;采用周围纹理抑制方法改进的Canny算子提取海界限区域的主要轮廓,并进行Hough变换而提取海天线或海岸线;依据海界线上的灰度环境判断背景,在划定线附近的局部区域,凭借该区域内海面灰度的平缓特性而对其进行聚类提取目标;分析剩余海面灰度的统计特征,求取属于海面区域的灰度范围,快速区分海面区域和非海面区域;最后,进行后续处理,以剔除伪目标并标记真实目标.结果表明,该方法处理单帧图像的平均耗时在100 ms以内,具有较好的准确性和实时性.  

关键词: 图像处理, 海界限区域, 周围纹理抑制, 聚类, 海面灰度范围

Abstract: A feasible method combining with the character of marine visible images was proposed to detect targets automatically in the sequential images from surface vehicle. It is not only suitable for small targets under seasky background but also for large targets under offshore background. First, the complexity of subimages and the average gray difference of their up and down neighborhood are measured to predict the sea line region, canny edge detection with surround suppression is applied to extract the contour of the region and Hough transforming is used to pick the longest line as sea line. There is no more processing if the image does not possess sea line region. Second, the region is defined as simple seasky background or complex offshore background according to the variance above the sea line. Clustering is implemented to extract the targets within the local region tailored by the sea line based on its smooth change of gray level. Third, gray characteristic of the rest sea is analyzed and sea gray range is obtained. Thus sea blocks and target blocks can be distinguished quickly. Finally, the segmented image is done with proper postprocessing in order to discard pseudo targets and mark the real targets. The experimental results prove that this method can locate the targets exactly. The time cost per frame is within 100 ms. It is robust and fast.  

Key words: image processing, sea line range, surround suppression, clustering, sea gray range

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