摘要
提出了一种被动式太赫兹图像识别算法。算法对原始太赫兹图像进行去噪预处理之后,通过对灰度直方图分析并对其曲线拟合,选定种子点和生长阈值对图像进行区域生长,以实现图像分割。实验结果证明,算法能够有效地从被动太赫兹图像背景中提取感兴趣的目标区域,有利于快速准确地发现被检测者隐藏在衣服内的违禁品,增强了安检成像系统的实用性。
This study puts forward an image segmentation algorithm for passive terahertz images. First of all, the captured original terahertz images are denoised in the preprocessing course. Afterwards, we select the seed regions and the growing criteria by analysis and curve fitting of the gray histogram of the denoised images, and then carry out region growing. Experiment results show that the proposed algorithm is able to extract regions of interest from background effectively, which could help to detect the contrabands hidden under the clothes of the target subjects quickly and accurately, and consequently strengthen the practicability of our imaging system.
出处
《强激光与粒子束》
EI
CAS
CSCD
北大核心
2013年第6期1597-1600,共4页
High Power Laser and Particle Beams
基金
国家自然科学基金项目(11004140)
光电成像技术与系统教育部重点实验室科研基地科技支撑计划项目(2012OEIOF04)
北京市教育委员会科技面上项目(11224010011)
关键词
被动式太赫兹成像
图像分割
曲线拟合
区域生长
passive terahertz imaging, image segmentation, curve fitting, region growing